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Does the cultural affinity of a group's members contribute to the group's collective intelligence?

Likely the 1,000's of you who have already submitted entries into the pending "HFC! CYPHIMU? contest, the winner of which will be awarded a beautiful  "I am a citizen of the Liberal Republic of Science/I ♥ Popper!”  t-shirt (Jon Baron currently sits atop the leader board, btw), are bored and wishing you had something else to do.  

Well how about this?

First, read this fascinating study of "c," a measure of intelligence that can be administered to a collective entity.

 The study was first published in Science (2 yrs ago; fortunately, one of the authors pulled me from the jaws of entropy and  brought the article to my attention only yesterday!).

The authors show that the "collective intelligence" of groups assigned to work on problem tasks admits of reliable measurement by indicators akin to the ones used to measure "individual intelligence." An influential measure of individual intelligence is called the "g factor," or simply g. Thus, the authors call their collective intelligence measure "c factor" or "c."

C is predicted in part by the average intelligence of the group's members and by the intelligence of its smartest (highest-scoring on g) member. That it would be is not so surprising, given existing work on the predictors of group decisionmaking proficiency.

The really cool thing (aside from the proof that it was possible to form a reliable and valid measure of c) was the authors' finding that other interesting individual group-member characteristics also make an important contribution to c. One of these was how many women are in the group (compare with the recent claim by female members of the Senate that part of the reason Congress is so dysfunctional is that aren't enough female members; maybe, maybe not).

Another was the average score of the groups' members on a "social sensitivity" scale. Social sensitivity here measures, in effect, how emotionally perceptive an individual is. The better group members were at "reading" other's intentions, the more cooperatively and productively they engaged one another, the researchers found. This disposition in turn raised the "collective intelligence" of the group -- that is, enabled it to solve more problems more efficiently.  

Not mind-blowingly surprising, either I suppose. But if you think that social science is mainly about establishing mind-blowingly counterintuitive things, you are wrong, and will believe lots of invalid studies. Social science is mainly about figuring out which competing plausible conjectures are true

The conjectures that informed and were supported by this cool study were merely amazingly interesting, amazingly thought provoking, and likely amazingly useful to boot.

Second, now tell me what you think the connection might be between c and cultural cognition.  

As every schoolboy and -girl today knows, "cultural cognition" refers to the tendency of individuals to conform their perceptions of risk and other policy-relevant facts to ones that predominate in their cultural group. CCP studies this phenomenon, using experiments and other empirical methods to identity the mechanisms it comprises.

It is often assumed -- indeed, sometimes I myself and other studying cultural cognition say -- that cultural cognition is a "bias."

In fact, I don't believe this.  I believe instead that cultural cognition is intrinsic, even essential, to human rationality.

The most remarkable feature of human rationality, I'd say, is that individuals are able to recognize what is collectively known.  

Particularly, when a society is lucky enough to recognize that science's way of knowing is the most reliable way to know things, collective knowledge can be immense.  What's known collectively will inevitably outstrip what any individual member of the society can ever comprehend on his or her own--even if that individual is a scientist!

Accordingly, as my colleague Frank Keil has emphasized, individuals can participate in collective knowledge -- something that itself is a condition of there being much of it -- only if they can figure out what's known without being able to understand it. In other words, they must become proficient at knowing who knows what.  The faculty of rational perception involved in being able to figure this out reliably is both essential and amazing.

Well, it turns out that people are simply better at exercising this rational faculty -- of being able to reliably determine who knows what about what-- when they are in groups of people with whom they share a cultural affinity.  Likely they are just better able to "read" such people -- to figure out who actually knows something & who is just bull shitting.

Likely, too, people are better at figuring who knows what about what in these sorts of affinity groups because they are less likely to fight with one another. Conflict will interfere with their ability to exchange knowledge with one another.

Actually, there's no reason to think people can exercise the faculty of perception involved in figuring out who knows what about what only within cultural affinity groups.

On the contrary, there is evidence that culturally diverse groups will actually do better than culturally homogeneous ones if they stay at it long enough to get through an initial rough patch and develop ways of interacting that are suited for discerning who knows what within their particular group.

But in the normal run of things, people probably won't, spontaneously, want to make the effort or simply won't (without a central coordination mechanism) be able to get through the initial friction, and so they will, in the main, tend to learn who knows what about what within affinity groups. That's where cultural cognition comes from.

Generally, too, it works --so long as the science communication environment is kept free of the sorts of contaminants that make culturally diverse groups come to see positions on particular facts -- like whether the earth is heating up or whether the HPV vaccine has health-destroying side effects -- as markers of group membership and loyalty. When that happens, the members of all cultural groups are destined to be collectively dumb as 12 shy of a dozen, and collectively very unwell off.

So now -- my question: do you suppose the cultural affinity of a groups' members is a predictor of c? That is, do you suppose c will be higher in groups whose members are more culturally homogeneous?

Or do you suppose that culturally diverse groups might do better -- even without a substantial period of interaction -- if their individual members "social sensitivity" scores are high enough to offset lack of cultural affinity?

Wouldn't these be interesting matters to investigate? Can you think of other interesting hypotheses?

What's that? You say you won't offer your views on this unless there is the possibility of winning a prize?.... Okay. Best answer will get this wonderful "Cultural Cognition Lab" t-shirt.


What is the "political economy forecast" for a carbon tax? What are the benefits of such a policy for containing climate change? ("HFC! CYPHIMU?" Episode No. 1)

In the spirit of CCP’s wildly popular feature, “WSMD? JA!,” I’m introducing a new interactive game for the site called: “Hi, fellow citizen! Can you please help increase my understanding?”—or “HFC! CYPHIMU?” The format will involve posting a question or set of related questions relating to a risk or policy-relevant fact that admits of scientific inquiry & then opening the comment section to answers. The questions might be ones that simply occur to me or ones that any of the 9 billion regular subscribers to this blog are curious about. The best answer, as determined by “Lil Hal,”™ a friendly, artificially intelligent robot being groomed for participation in the Loebner Prize competition, will win a “Citizen of the Liberal Republic of Science/I Popper!” t-shirt!

I have a couple of questions  that I’m simply curious about and hoping people can help me to figure out the answers to.

BTW, I’m using “figuring out the answer” as a term of art.

It doesn’t literally mean figuring out the answer! I think questions to which “the answer” can be demonstrably “figured out” tend not to be so interesting as ones that we believe do have answers but that we agree turn on factors that do no admit of direct observation, forcing us to draw inferences from observable, indirect evidence. For those, we have to try to "figure out" the answer in a disciplined empirical way by (1) searching for observable pieces of evidence that we believe are more consistent with one answer than another, (2) combining that evidence with all the other evidence that we have so that we can (3) form a provisional answer (one we might well be willing to act on if necessary) that is itself (4) subject to revision in light of whatever additional evidence of this sort we might encounter.

Accordingly, any response that identifies evidence that furnishes reason for treating potential answers as more likely or less than we might regard them without such evidence counts as “figuring out the answer.” Answers don’t have to be presented as definitive; indeed, if they are, that would likely be a sign that they aren’t helping to “figure out” in the indicated sense!

Oh-- answers that identify multiple sources of evidence, some of which make one answer more likely and some less relative to a competing one, will be awarded "I'm not afraid to live in a complex universe!" bonus points.

Okay, here are my “questions”:

a. If one is assessing the prospects for enacting a carbon tax (or some comparable form of national legislation aimed at reducing U.S. CO2 emissions), how big a factor is public opinion in favor of “doing something to address climate change”?

b. How much of a contribution would a carbon tax—or any other U.S. policy aimed at reducing the impact of atmospheric concentrations of CO2—make to mitigating or constraining global temperature increases or adverse impacts therefrom?

Some explanation for the questions will likely help to elicit answers of the sort I am interested in:

a. If one is assessing the prospects for enacting a carbon tax (or some comparable form of national legislation aimed at reducing U.S. CO2 emissions), how big a factor is public opinion in favor of “doing something to address climate change”?

This is essentially a political economy question.

Researchers who have performed opinion surveys often present evidence that there is growing public support—and possibly even “majority” support—in the U.S. for policies that would constructively address the risks posed by climate change. This conclusion—and for this question, please accept it as correct even if you doubt the methods of these researchers —is in turn treated as support for the proposition that efforts to enact a carbon tax or similar legislation aimed at reducing carbon emissions in the U.S. are meaningfully likely to succeed.

Of course, we all know that “majority public support” does not necessarily translate in any straightforward sense into adoption of policies. If it did, the U.S. would have enacted “gun control” measures in the 1970s or 1980s much stricter than the ones President Obama is now proposing. We’d have a muscular regime of campaign-finance regulations. We wouldn’t have massive farm subsidies, and tax loopholes that enable major corporations to pay (literally) no U.S. income tax. Etc.

The “political economy climate” is complex—if not as complex as the natural one, then pretty close! Forecasts of what is likely or possible depend on the interaction of many variables, of which “public support” is only one.

So, can you please help me increase my understanding? What is the political-economy model that informs the judgment of those who do believe increased public support for “action on climate change” meaningfully increase the likelihood of a carbon tax? What are the mechanisms and practical steps that will translate this support into enactment of policy?

b. How much of a contribution would a carbon tax—or any other U.S. policy aimed at reducing the impact of atmospheric concentrations of carbon—make to mitigating or constraining global temperature increases or adverse impacts therefrom?

This, obviously, is a “climate science” question, primarily, although it might also be a political economy question.

The motivation behind the question consists of a couple of premises. One is that the U.S. is not the only contributor to atmospheric CO2; indeed, China has apparently overtaken us as the leader, and developing countries, most importantly India, will generate more and more greenhouse gases (not just CO2, but others, like Freon) as they seek to improve conditions of living for their members.

The second is scientific evidence relating to the climate impact of best-case scenarios on future atmospheric CO2 levels. Such evidence, as I understand it (from studies published in journals like Nature and the Proceedings of the National Academy of Sciences) suggests that earlier scientific projections of the contribution that CO2 reductions and ceilings can make to forestalling major, adverse impacts were too optimistic. Even if the U.S. stopped producing any CO2—even if all nations in the world did—there’d still be catastrophic effects as a result of climate change.

As an editorial in Nature put it,

The fossil fuels burned up so far have already committed the world to a serious amount of climate change, even if carbon emissions were somehow to cease overnight. And given the current economic turmoil, the wherewithal to adapt to these changes is in short supply, especially among the world's poor nations. Adaptation measures will be needed in rich and poor countries alike — but those that have grown wealthy through the past emission of carbon have a moral duty to help those now threatened by that legacy.

The latest scientific research suggests that even a complete halt to carbon pollution would not bring the world's temperatures down substantially for several centuries. If further research reveals that a prolonged period of elevated temperatures would endanger the polar ice sheets, or otherwise destabilize the Earth system, nations may have to contemplate actively removing CO2from the atmosphere. Indeed, the United Nations Intergovernmental Panel on Climate Change is already developing scenarios for the idea that long-term safety may require sucking up carbon, and various innovators and entrepreneurs are developing technologies that might be able to accomplish that feat. At the moment, those technologies seem ruinously expensive and technically difficult. But if the very steep learning curve can be climbed, then the benefits will be great.

I’m curious, then, what is the practical understanding of how a carbon tax or any other policy to reduce CO2 emissions in the U.S. will contribute to “doing something about climate change.”

Am I incorrect to think that such steps by themselves will not contribute in any material way?

If so, is the idea that U.S. efforts to constrain emissions will spur other nations to limit their output? What is the international political economy model for that expectation?

Even if other nations do enact measures that make comparable contributions to limiting atmospheric CO2 emissions, how much of a difference will that make given, as the Nature editorial puts it, “[t]he latest scientific research suggests that even a complete halt to carbon pollution would not bring the world's temperatures down substantially for several centuries?”

Thanks to anyone who can help make me smarter on these issues!


A case study: the HPV vaccine disaster (Science of Science Communication Course, Session 1)

This semester I'm teaching a course entitled the Science of Science Communication. I've posted general information on the course and will be posting the reading list at regular intervals. I will also post syntheses of the readings and the (provisional, as always) impressions I have formed based on them and on class discussion. This is this first such synthesis. I eagerly invite others to offer their own views, particularly if they are at variance with my own, and to call attention to additional sources that can inform understanding of the particular topic in question and of the scientific study of science communication in general. 


1. The HPV vaccine disaster

HPV stands for human papilomavirus. It is a sexually transmitted disease.

The infection rate is extremely high: 45% for women in their twenties, and almost certainly just as high for men, in whom the disease cannot reliably be identified by test.

The vast majority of people who get HPV experience no symptoms.

But some get genital warts.

And some get cervical cancer.

Some of them--over 3500 women per yr in U.S. -- die. 

In 2006, the FDA approved an HPV vaccine, Gardasil, manufactured by the New Jersey pharmaceutical firm Merck. Gardasil is believed to confer immunity to 70% of the HPV strains that cause cervical cancer. The vaccine was approved only for women, because only in women had HPV been linked to a “serious disease” (cervical cancer), a condition of eligibility for the fast-track approval procedures that Merck applied for. Shortly after FDA approval, the Center for Disease Control recommended universal vaccination for adolescent girls and young women.

The initial public response featured intense division. The conflict centered on proposals to add the vaccine—for girls only—to the schedule of mandatory immunizations required for middle school enrollment. Conservative religious groups and other mandate opponents challenged evidence of the effectiveness of Gardasil and raised concerns about unanticipated (or undisclosed) side-effects. They also argued that vaccination would increase teen pregnancy and other STDs by investing teenage girls with a false sense of security that would lull them into engaging in unprotected, promiscuous sex. Led by women’s advocacy groups, mandate proponents dismissed these arguments as pretexts, motivated by animosity toward violation of traditional gender norms.

In 2007, Texas briefly became the first state with a mandatory vaccination requirement when Governor Perry—a conservative Republican aligned with the religious right—enacted one by executive order. When news surfaced that Perry had accepted campaign contributions from Merck (which also had hired one of Perry’s top aids to lobby him), the state legislature angrily overturned the order.

Soon thereafter, additional stories appeared disclosing the major, largely behind-the-scene operation of the pharmaceutical company in the national campaign to enact mandatory vaccination programs.  Many opinion leaders who previously had advocated the vaccine now became critics of the company, which announced that it was “suspending” its “lobbying” activity. Dozens of states rejected mandatory vaccination, which was implemented in only one, Virginia, where Merck had agreed to build a vaccine-manufacturing facility, plus the District of Columbia.

Current public opinion is characterized less by division than by deep ambivalence. Some states have enacted programs subsidizing voluntary vaccination, which in other states is covered by insurance and furnished free of cost to uninsured families by various governmental and private groups. Nevertheless, “uptake” (public health speak for vaccination rate) among adolescent girls and young women is substantially lower here (32%) than it is in nations with inferior public health systems, including ones that likewise have failed to make vaccination compulsory (e.g., Mexico, 67%, and Portugal, 81%). The vaccination rate for boys, for whom the FDA approved Gardasil in 2009, is a dismal 7%.

2. What’s the issue? (What “disaster”?)

The American pubic tends to have tremendous confidence in the medical profession, and is not hostile to vaccinations, mandatory or otherwise (I’ll say more about the “anti-vaccine movement” another time but for now let’s just say it is quite small). When the CDC recommended vaccination for H1N1 in December 2009, for example, polls showed that a majority of the U.S. population intended to get the vaccine, which ran out before the highest-risk members of the population—children and the elderly—were fully inoculated. In a typical flu season, uptake rates for children usually exceed 50%.

The flu, of course, is not an STD. But Hepatitis B is. The vast majority of states implemented mandatory HBV vaccination programs—without fuss, via administrative directives issued by public health professionals—after the CDC recommended universal immunization of infants in 1995. Like the HPV vaccine, the HBV vaccine involves a course of two to three injections.  National coverage for children is over 90%.

There are (it seems to me!) arguments that a sensible sexually active young adult could understandably, defensibly credit for forgoing the HPV vaccination, and that reasonable parents and reasonable citizens could for not having the vaccine administered to their children and mandated for others’. But the arguments are no stronger than—not not at all different from—the ones that could be made against HBV vaccination. They don’t explain, then, why in the case of the HPV vaccine the public didn’t react with its business-as-usual acceptance when public health officials recommended that children and young adults be vaccinated.

What does? That question needs an answer regardless of how one feels about the HPV vaccine or the public reaction to it—indeed, in order even to know how one should feel about those matters.

3. A polluted science communication environment

The answer—or at least one that is both plausible and supported by empirical evidence—is the contamination of the “science communication environment.”  People are generally remarkably proficient at figuring out who knows what; they are experts in identifying who the experts are and reliably discerning what those with expertise counsel them to do. But that capacity—that faculty of reasoning and perception—becomes disabled (confused, unreliable) when an empirical fact that admits of scientific investigation provokes controversy among groups united by shared values and perspectives.

Most of us have witnessed this situation via casual observation; scholars who carefully looked at parents trying to figure out what to think about the HPV vaccine saw that they were in that situation. They saw, for example, the mixture of shame and confusion experienced by an individual mother who acknowledged (admitted; confessed?) in the midst of a luncheon conversation with scandalized friends (also mothers) that she had allowed her middle-school daughter to be vaccinated (“what--why? . . .”; “Well, because that’s what the doctor advised . . . .” “Then, you had better find a new doctor, dear . . . . ”).

Scholars using more stylized but more controlled methods to investigate how people form perceptions of the HPV vaccine report the same thing.  In one, researchers tested how exposure to two versions of a fictional news articles affected public support for mandatory HPV vaccination.  Both versions described (real) support for mandatory vaccination by public health experts. But one, in addition, adverted without elaboration to “medical and political conflict” surrounding a mandatory-vaccine proposal. The group exposed to the “controversy” version of the report were less likely to support the proposal—indeed, on the whole were inclined to oppose it—than those in the “no controversy” group. This effect, moreover, was as strong among subjects inclined to support mandatory vaccination policies generally as among those who weren’t/

The study result admits (I admit!) of more than one plausible explanation. But one is that being advised the matter was “politically controversial” operated as a cue that generated hesitation to credit evidence of expert opinion among people otherwise disposed to use it as their guide on public health issues.

Another study done by CCP bolsters this interpretation. That one assessed how members of the public with diverse cultural outlooks assessed information about the risks and benefits of HPV vaccination. Subjects of opposing worldviews were inclined to form opposing beliefs when evaluating information on the risks and benefits of the vaccine. Yet the single most important factor for all subjects, the study found, was the position taken by “public health experts.” Sensibly & not surprisingly, people of diverse values share the disposition to figure out what credible, knowledge experts are saying on things that they themselves lack the expertise to understand but that are important for the wellbeing of themselves and others.

Whether the subjects viewed experts as credible and trustworthy, however, was highly sensitive to their tacit perception of the experts’ cultural values. This didn’t actually have much impact on subjects’ risk perceptions--unless they were exposed to alignments of arguments and (culturally identifiable) experts that gave them reason to think the issue was one that pit members of their group against another in a pattern that reinforced the subjects’ own cultural predispositions toward the HPV vaccine. That’s when the subjects became massively polarized.

That’s the situation, moreover, that people in the world saw, too. From the moment culturally diverse citizens first tuned in, the signal they were getting on the science-communication frequency of their choice was that “they say this; we, on the other hand, really know that.” 

Under these conditions, the manner in which people evaluate risk is psychologically equivalent to the one in which fans of opposing football teams form their impressions of whether the receiver who caught the last-second, hail-Mary pass was out of bounds or in.  Anyone who thinks this is the right way to for people to engage information of consequence to their collective well-being—or who thinks that people actually want to form their beliefs this way—is a cretin, no matter what he or she believes about the HPV vaccine.

4. An avoidable “accident”

There was nothing necessary about the HPV vaccine disaster.  The HPV vaccine took a path different from the ones travelled by the H1N1 vaccine in 2009, and by the HBV vaccine in 1995 to the present, as a result of foreseeably bad decisions, stemming from a combination of strategic behavior, gullibility, and collective incapacity.

Information about the risks and benefits of HPV vaccine came bundled with facts bearing culturally charged resonances. It was a vaccine for 11-12 year old girls to prevent contraction of a sexually transmitted disease.  There was a proposal to make the vaccine mandatory as a condition of school enrollment.  The opposing stances of iconic cultural antagonists were formed in response to (no doubt to exploit the conflictual energy of) the meanings latent in these facts—and their stances became cues for ordinary, largely apolitical individuals of diverse cultural identities.

These conditions were all an artifact of decisions Merck self-consciously made about how to pursue regulatory approval and subsequent marketing of Gardasil. It sought approval of the vaccine for girls and young women only in order to invoke “fast track” consideration by the FDA. It thereafter funded—orchestrated, in a manner that shielded its own involvement—the campaign to promote adoption of mandatory vaccination programs across the states.  To try to “counterspin” the predictable political opposition to the vaccine, it hired an inept sock puppet—“Oops!”—whose feebly scripted performance itself enriched the cultural resources available to those seeking to block the vaccine.

Had Merck not sought fast-track approval and pushed aggressively for quick adoption of mandatory vaccination programs, the FDA would have approved the vaccine for males and females just a few years later, insurance companies plus nongovernmental providers would have furnished mechanisms for universal vaccination sufficient to fill in any gaps in stated mandates, which would have been enacted or not by state public health administrators largely removed from politics. Religious groups—which actually did not oppose FDA approval of the HPV vaccine but only the proposal to mandate it—wouldn’t have had much motivation or basis for opposing such a regime.

As a result, parents would have learned about the risk and benefits of the HPV vaccine from medical experts of their own choosing—ones chosen by them, presumably, because they trusted them—without the disorienting, distracting influence of cultural conflict. They would have learned about it, in other words, in the same conditions as the ones in which they now encounter the same sort of information on the HBV and other vaccines. That would have been good for them.

But it wouldn’t have been good for Merck. For by then, GlaxoSmithKline’s alternative vaccine would have been ready for agency approval, too, and could have competed free of the disadvantage of what Merck hoped would be a nationwide set of contracts to supply Gardasil to state school systems.

Is this 20/20 hindsight? Not really; it is what many members of the nation’s public health community saw at the time. Many who supported approval of Gardasil still opposed mandatory vaccination, both on the grounds that it was not necessary for public health and likely to back fire. Even many supporters of such programs—writing in publications such as the New England Journal of Medicine—conceded that “vaccination mandates are aimed more at protecting the vaccinee than at achieving herd immunity”—the same economic-subsidy rationale that was deemed decisive for mandating HPB vaccination.

These arguments weren’t rejected so much as never even considered meaningfully. Those involved in the FDA and CDC approval process weren’t charged with and didn’t have the expertise to evaluate how the science communication environment would be affected by the conditions under which the vaccine was introduced.

So in that sense, the disaster wasn’t their “fault.” It was, instead, just a foreseeable consequence of not having a mechanism in our public health system for making use of the intelligence and judgment at our disposal for dealing with science communication problems that are actually foreseen.

Whose fault will it be if this happens again?

5. Wasted knowledge

The likely “public acceptance” of an HPV vaccine was something that public health researchers had been studying for years before Gardasil was approved. But the risk that public acceptance would be undermined by a poisonous science communication environment was not something that those researchers warned anyone about. 

Instead, they reported (consistently, in scores of studies) that acceptance would turn on parents’ perceptions of the cost of the vaccine, its health benefits, and its risks, all of which would be shaped decisively by parents’ deference to medical expert opinion. 

This advice was worse than banal; it was disarmingly misleading. Public health researchers anticipated that a vaccine would be approved only if effective and not unduly risky, and that it would be covered by insurance and economically subsidized by the government. Those were reasonable assumptions. What wasn’t reasonable was the fallacious conclusion (present in study after study) that therefore all public health officials would have to do to promote “public acceptance” was tell people exactly these things. 

Things don’t work that way. And I’m not announcing any sort of late-breaking, hot-off- the-press-of-Nature-or-Science-or-PNAS news when I say that.

Social psychology and related disciplines are filled with knowledge about the conditions that determine how ordinary, intelligent people make sense of information about risk and identify who they can trust & when to give them expert advice.  The public health literature is filled with evidence of the importance of social influences on public perceptions of risks—e.g., those associated with unsafe sex and smoking. 

That knowledge could have been used to generate insight that public health officials could have used to forecast the impact of introducing Gardasil in the way it was introduced.

It wasn’t. That scientific knowledge on science communication was wasted. As a result, much of the value associated with the medical science knowledge that generated Gardasil has been wasted too. 

Session reading list.


What inferences can be drawn from *empirical evidence* about the science-communication impact of using the term "climate change denier"?

Andy "dotearth" Revkin, the Hank Aaron of environmental-science journalism, posted this question after a colloquy with other thoughtful science communicators. Andy apparently was moved to ask it after observing a talk on climate change by "science guy" Bill Nye.

Here is my answer. I invite others to supplement!

As is so for climate change, sometimes positions on a risk or other policy-consequential fact become publicly recognizable symbols of membership in opposing cultural groups. When that happens, members of those groups are likely to judge the expertise of any science communicator who is addressing that risk based on whether they see him or her as aligned with or hostile to their own group.  E.g., see  

1. Corner, A., Whitmarsh, L., & Xenias, D. Uncertainty, scepticism and attitudes towards climate change: biased assimilation and attitude polarisation. Climatic Change, 1-16. doi: 10.1007/s10584-012-0424-6

2. Kahan, D., Braman, D., Cohen, G., Gastil, J., & Slovic, P. (2010). Who Fears the HPV Vaccine, Who Doesn’t, and Why? An Experimental Study of the Mechanisms of Cultural Cognition. Law and Human Behavior, 34(6), 501-516.

3. Kahan, D. M., Jenkins-Smith, H., & Braman, D. (2011). Cultural Cognition of Scientific Consensus. J. Risk Res., 14, 147-174.

This helps explain why even people who are pro-science & who believe science should inform public policy generally can polarize on a policy-consequential fact that admits of scientific evidence (an effect that persists even among highly science literate members of opposing groups).

Accordingly, whether or not he "alienates" anyone, I think when someone like Bill Nye speaks about "climate change deniers" he creates the foreseeable risk that many ordinary people, including many reflective and open-minded ones, will not view him as credible. "Climate denial," for them,  is likely to be a cue that causes them to perceive Nye (perhaps rightly, but perhaps wrongly) as aligned with a cultural group that harbors animosty toward their own. They will thus not view him as a genuine (or at least not as a trustworthy) "expert" but instead seem him as a partisan.  Consistent with Brendan Nyhan's recent study, exposure to Nye's advocacy might even intensify the strength with which ordinary people are committed to the position he is attacking.

These are conjectures, extrapolations from the results of studies that are in effect models of how people process information in such settings.  One could test my view by taking a recording of Nye's remarks and showing it to a general population sample. If those who observed him became more culturally polarized relative to a control group who didn't see Nye's remarks, that would be evidence supportive of the hypothesis I just offered, whereas if they didn't polarize or even started to converge relative to the control group, that would be evidence the other way.  I'm happy to advise or collobarate w/ anyone who would like to do the study (including Bill Nye, provided he gives me one of his cool ties).

Such a test would still only be a model, btw, from which conclusions about how to talk to whom about what (assuming one actually wants to have a meaningful exchange of ideas with someone) would still depend on inferences reflecting information, evidence, beliefs, etc. independent of the study itself. That's the way things are, always and on everything that one can study with empirical methods (this is obvious but it bears repeating -- over & over & over -- because many people have the unscientific view that scientific studies "prove/disprove" propositions & "demonstrate" the wisdom of courses of action in some way that obviates the need to rely on judgment and reason, not to mention the need ever to consider any more evidence ever again).


Yale University "Science of Science Communication" course

Am teaching this course this semester:

PSYC 601b. The Science of Science Communication. The simple dissemination of valid scientific knowledge does not guarantee it will be recognized by nonexperts to whom it is of consequence. The science of science communication is an emerging, multidisciplinary field that investigates the processes that enable ordinary citizens to form beliefs consistent with the best available scientific evidence, the conditions that impede the formation of such beliefs, and the strategies that can be employed to avoid or ameliorate such conditions. This seminar will survey, and make a modest attempt to systematize, the growing body of work in this area. Special attention will be paid to identifying the distinctive communication dynamics of the diverse contexts in which nonexperts engage scientific information, including electoral politics, governmental policymaking, and personal health decision making. 

Here's a "manifesto" of sorts, which comes from course syllabus:

1. Overview. The most effective way to communicate the nature of this course is to identify its motivation.  We live in a place and at a time in which we have ready access to information—scientific information—of unprecedented value for our individual and collective welfare. But the proportion of this information that is effectively used—by individuals and by society—is shockingly small. The evidence for this conclusion is reflected in the manifestly awful decisions people make, and outcomes they suffer as a result, in their personal health and financial planning. It is reflected too not only in the failure of governmental institutions to utilize the best available scientific evidence that bears on the safety, security, and prosperity of its members, but in the inability of citizens and their representatives even to agree on what that evidence is or what it signifies for the policy tradeoffs acting on it necessarily entails.

This course is about remedying this state of affairs. Its premise is that the effective transmission of consequential scientific knowledge to deliberating individuals and groups is itself a matter that admits of, and indeed demands, scientific study.  The use of empirical methods is necessary to generate an understanding of the social and psychological dynamics that govern how people (members of the public, but experts too) come to know what is known to science. Such methods are also necessary to comprehend the social and political dynamics that determine whether the best evidence we have on how to communicate science becomes integrated into how we do science and how we make decisions, individual and collective, that are or should be informed by science.

Likely you get this already: but this course is not simply about how scientists can avoid speaking in jargony language when addressing the public or how journalists can communicate technical matters in comprehensible ways without mangling the facts.  Those are only two of many "science communication problems," and as important as they are, they are likely not the ones in most urgent need of study (I myself think science journalists have their craft well in hand).  Indeed, in addition to dispelling (assaulting) the fallacy that science communication is not a matter that requires its own science, this course will self-consciously attack the notion that the sort of scientific insight necessary to guide science communication is unitary, or uniform across contexts—as if the same techniques that might help a modestly numerate individual understand the probabilistic elements of a decision to undergo a risky medical procedure were exactly the same ones needed to dispel polarization over climate science! We will try to individuate the separate domains in which a science of science communication is needed, and take stock of what is known, and what isn’t but needs to be, in each.

The primary aim of the course comprises these matters; a secondary aim is to acquire a facility with the empirical methods on which the science of science communication depends.  You will not have to do empirical analyses of any particular sort in this class. But you will have to make sense of many kinds.  No matter what your primary area of study is—even if it is one that doesn’t involve empirical methods—you can do this.  If you don’t yet understand that, then perhaps that is the most important thing you will learn in the course. Accordingly, while we will not approach study of empirical methods in a methodical way, we will always engage critically the sorts of methods that are being used in the studies we examine, and from time to time I will supplement readings with more general ones relating to methods.  Mainly, though, I will try to enable you to see (by seeing yourself and others doing it) that apprehending the significance of empirical work depends on recognizing when and how inferences can be drawn from observation: if you know this, you can learn whatever more is necessary to appreciate how particular empirical methods contribute to insight; if you don’t know this, nothing you understand about methods will furnish you with reliable guidance (just watch how much foolishness empirical methods separated from reflective, grounded inference can involve).

Will post course info & weekly reading lists (not readings themselves, sadly, since they consist mainly of journal articles that it would violate Yale University licensing agreement for me to distribute hither & yon; I certainly don't want the feds coming down on me for the horrible crime of making knowledge freely available!)

First session was yesterday & topic was HPV vaccine. It was great class.  Plan to post some reflections on reading & discussion soon. But have to go running now!



Amazingly cool & important article on virulence of ideologically motivated reasoning

Political psychologist Brendan Nyhan  and his collaborators Jason Reifler & Peter Ubel just published a really cool paper in Medical Care entitled “The Hazards of Correcting Myths About Health Care Reform.” It shows just how astonishingly resistant the disease of ideologically motivated reasoning is to treatment with accurate information. And like all really good studies, it raises some really intersting questions.

NRU conducted an experiment on the effect of corrections of factually erroneous information originating from a partisan source. Two groups of subjects got a news article that reported on false assertions by Sarah Palin relating to the role of “death panels” in the Obamacare national health plan.  One group received in addition a news story that reported that “nonpartisan health care experts have concluded that Palin was wrong.”  NRU then compared the perceptions of the two groups.

Well, one thing they found is that the more subjects liked Palin, the more likely they were to believe Palin’s bogus “death panel” claims.  Sure, not a big surprise.

They also found that the impact of being showing the “correction” was conditional on how much subjects liked Palin: the more they liked her, the less they credited the correction. Cool, but again not startling.

What was mind-blowing, however, was the interaction of these effects with political knowledge.  As subjects became more pro-Palin in their feelings, high political knowledge subjects did not merely discount the “correction” by a larger amount than low political knowledge ones. Being exposed to the “nonpartisan experts say Palin wrong” message actually made high-knowledge subjects with pro-Palin sentiments credit her initially false statements even more strongly than their counterparts in the “uncorrected” or control condition!

The most straightforward interpretation is that for people who have the sort of disposition that “high political knowledge” measures,  the “fact check”-style correction itself operated as a cue that the truth of Palin's statements was a matter of partisan significance, thereby generating unconscious motivation in them to view her statements as true.

That’s singularly awful.

There was already plenty of reason to believe that just bombarding people with more and more “sound information” doesn’t neutralize polarization on culturally charged issues like climate change, gun control, nuclear power, etc. 

There was also plenty of reason to think that individuals who are high in political knowledge are especially likely to display motivated reasoning and thus to be especially resistant to a simple “sound information” bombardment strategy.

But what NRU show is that things have become so bad in our polarized society that trying to correct partisan-motivated misperceptions of facts can actually make things worse!  Responding to partisan misinformation with truth is akin to trying to douse a grease fire with water!

But really, I’d say that the experiment shows only potentially how bad things can get.

First, the NRU experimental design, like all experimental designs, is a model of real-world dynamics.  I’d say the real-world setting it is modeling is one in which an issue is exquisitely fraught; Palin & Obamacare are each flammable enough on their own, so when you mix them together you’ve created an atmosphere just a match strike away from an immense combustion of ideologically motivated reasoning.

Still, there is plenty of reason to believe that there are conditions, issues, etc.  like that in the world. So the NRU model gives us reason to be very wary of rushing around trying to expose “lies” as a strategy for correcting misinformation.  At least sometimes, the the study cautions, you could be playing right into the misinformer’s hands.

Actually, I think that this is the scenario on the mind of those who’ve reacted negatively to the proposed use of climate change “truth squads”—SWAT teams of expert scientists who would be deployed to slap down every misrepresentation made by individuals or groups who misrepresent climate science.  The NRU study gives more reason to think those who didn’t like this proposal were right to think this device would only amplify the signal on which polarization feeds.

Second, interpreting NRU, however, depends in part on what is being measured by “political knowledge.”

Measured with a civics quiz, essentially, “political knowledge” is well-known to amplify partisanship.

But why exactly?

The usual explanation is that people who are “high” in political knowledge literally just know more and hence assign political significance to information in a more accurate and reliable way. This by itself doesn’t sound so bad. People’s political views should reflect their values, and if getting the right fit requires information, then the "high" political knowledge individuals are engaged in better reasoning. Low-knowledge people bumble along and thus form incoherent views.

But that doesn’t seem satisfying when one examines how political knowledge can amplify motivated reasoning.  When people engage in ideologically motivated reasoning, they give information the effect that gratifies their values independently of whether doing so generates accurate beliefs.  Why would knowing more about political issues make people reason in this biased way?

Another explanation would be that “political knowledge” is actually measuring the disposition to define oneself in partisan terms. In that case, it would make sense to think of high knowledge as diagnostic or predictive of vulnerability to ideologically motivated reasoning. People with strong partisan identities are the ones who experience strong unconscious motivation to use what they know in a way that reinforces conclusions that are ideologically congenial.

Moreover, in that case, being low in “political knowledge” arguably makes one a better civic reasoner. Because one doesn’t define oneself so centrally with respect to one’s ideology or party membership, one gives information an effect that is more reliably connected to its connection to truth.  Indeed, in NRU the “low knowledge” subjects seemed to be responding to “corrections” of misinformation in a normatively more desirable way—assuming what we desire is the reliable recognition and open-minded consideration of valid evidence. 

I would say that the “partisan identity” interpretation of political knowledge is almost certainly correct, but that the “knows more, reasons better” interpretation is likely correct too.  The theoretical framework that informs cultural cognition asserts that it is rational for people to regard politically charged information in a manner that reliably connects their beliefs to those that predominate in their group because the cost of being “out of synch” on a contentious matter is likely to be much higher than the cost of being “wrong”—something that on most political issues is costless to individuals, given how little impact their personal beliefs have on policymaking.  If so, then, we should expect people who “know more” and “reason better” to be more reliable in “figuring out” what the political significance of information is—and thus more likely to display motivated reasoning.

In support of this, I’d cite two CCP studies. The first showed that individuals who have higher levels of science comprehension are more likely to polarize on climate change. The second shows that individuals who are higher in “cognitive reflection,” as measured by the CRT test, show an even greater tendency to engage in culturally or ideologically motivated reasoning when evaluating information.

These studies belie an interpretation of NRU that suggests that “low knowledge” subjects are reasoning in a higher quality way because they are not displaying motivated cognition.  In truth, higher quality reasoning makes motivated reasoning worse.

Because it is rational for people to fit their perceptions of risk and other policy-consequential facts to their identities (indeed, because this is integral to their capacity to participate in collective knowledge), the way to avert political conflict over policy-relevant science isn't to flood the political landscape with "information." It is to protect the science communication enviroment from the antagonistic social meanings that are the source of the conflict between the individual interest that individuals have in forming and expressing commitment to particular cultural groups and the collective one that the members of all such groups have in converging on the best available evidence of how to secure their common ends.

What gives me pause, though, is an amazingly good book that I happen to be reading right now: The Ambivalent Partisan by Lavine, Johnston & Steenbergen. LJS reports empirical results identifying a class of people who don’t define themselves in strongly partisan terms, who engage in high quality reasoning (heuristic and systematic) when examining policy-relevant evidence, and who are largely immune to motivated reasoning.  

That would make these ambivalent partisans models of civic virtue in the Liberal Republic of Science. I suppose it would mean too that we ought to go on a crash program to study these people and see if we could concoct a vaccine, or perhaps a genetic modification procedure, to inculcate these dispositions in others. And more seriously still (to me at least!), such findings might suggest that I need to completely rethink my understanding of  cultural cognition as integral to rational engagement with information at an individual level. . . . I will give a fuller report on LJS in due course.

I can report for now, though, that NRU & LJS have both enhanced my knowledge and made me more confused about things I thought I was figuring out. 

Important contributions to scholarly conversation tend to have exactly that effect!


Delli Carpini, M.X. & Keeter, S. What Americans Know About Politics and Why It Matters. (Yale University Press, New Haven; 1996).

Hovland, C.I. & Weiss, W. The Influence of Source Credibility on Communication Effectiveness. Public Opin Quart 15, 635-650 (1951-52).

Kahan, D. Fixing the Communications Failure. Nature 463, 296-297 (2010).

Kahan, D. Ideology, Cognitive Reflection, and Motivated Cognition, CCP Working Paper No. 107 (Nov. 29, 2012).

Kahan, D. Why we are poles apart on climate change. Nature 488, 255 (2012).

Kahan, D.M., Peters, E., Wittlin, M., Slovic, P., Ouellette, L.L., Braman, D. & Mandel, G. The polarizing impact of science literacy and numeracy on perceived climate change risks. Nature Climate Change 2, 732-735 (2012).

Lavine, H., Johnston, C.D. & Steenbergen, M.R. The ambivalent partisan : how critical loyalty promotes democracy. (Oxford University Press, New York, NY; 2012).

Nyhan, B., Reifler, J. & Ubel, P.A. The Hazards of Correcting Myths About Health Care Reform. Medical Care Publish Ahead of Print, 10.1097/MLR.1090b1013e318279486b (9000).

Zaller, J.R. The Nature and Origins of Mass Opinion. (Cambridge Univ. Press, Cambridge, England; 1992).



An interesting story: on whether "strengthening self-defense law deters crime"

Scholars in the social sciences and related disciplines (including law) often circulate “working papers” –basically, rough drafts of their articles. The main reason is to give other scholars a chance to read and offer comments, which authors can then use to improve their work.

Scholars value the chance to make their papers as strong as possible before submitting them for peer review. And they for sure don’t want to end up publishing something that later is shown to be flawed.

In response to a recent blog, a commenter called my attention to a draft paper that reports the results of a study of “stand your ground” laws. These laws provide that a person who honestly and reasonably believes that he or she faces an imminent threat of death or great bodily harm doesn’t have to retreat before resorting to deadly force in self-defense.  Numerous states have enacted such laws in the last decade in response to a campaign orchestrated by the National Rifle Association to promote their adoption.

The study investigates a really interesting question: what effect did enacting a“stand your ground” law have in states that had previously imposed a “duty to retreat”—ones, in other words, that before had restricted the right to use deadly force to circumstances in which a person could not have been expected to escape an attack by fleeing? As the authors (economists, by training) put it:

These laws alter incentives in two important ways. First, the laws reduce the expected cost of using lethal force. . . . In addition, the laws increase the expected cost of committing violent crime, as victims are more likely to respond by using lethal force.  The purpose of our paper is to examine empirically whether people reasoned to these incentives, and thus whether the laws lead to an increase in homicide, or to deterrence of crime more generally.

Using multivariate regression analysis, the study found that homicides went up in these states. The “stand your ground” standard, in other words, makes people less safe, not more.

This finding has received considerable media attention, in large part because a debate has been raging about the impact of “stand your ground” laws on homicide rates since the murder of Trayvon Martin in Florida last spring.

There’s only one problem. The majority of the states that enacted “stand your ground” laws already permitted citizens to use deadly force to repel a lethal attack regardless of the possibility of safe retreat.  The law in these states didn’t change when they enacted the statutes.

The paper lists 21 states in which it says enactment of “stand your ground laws” “remove[d] [the] duty to retreat ... outside the home.” 

Not true—or less than 50% true, in any case.

I’ve prepared a list (click on the thumbnail to inspect it) that identifies pre-“stand your ground” law judicial decisions (self-defense is one of those legal doctrines that traditionally has gotten worked out by judges) in 11 of these states. They all indicate clearly that a person needn’t retreat before resorting to deadly force to repel a potentially lethal assault in a public place. (Do realize my research wasn't exhaustive, as it would be if I were writing an academic paper as opposed to a blog post!)

But hey, put scholarly errors aside for a second. There’s an interesting story here, and I can’t resist sharing it with you!

The traditional “common law” doctrine of self-defense that U.S. states inherited from England was that a person had a duty to “retreat to the wall” before using deadly force against another. But in the late 19th Century and early 20th, many U.S. states in the South and West rejected this position and adopted what became known as the “true man” doctrine. 

The idea was that that a man whose character is true—that is, straight, not warped; as in “true beam”—appropriately values his own liberty and honor more than the life of a person who wrongfully attacks him in a public place.  Punishing an honorable man for behaving honorably, one of the early authorities explained, is contrary to the“ 'the tendency of the American mind' ” (Beard v. United States, 158 U.S. 550, 561 (1895) (Harlan, J) (quoting Erwin v. State, 29 Ohio St. 186, 193, 199 (1876)).  

 “It is true, human life is sacred, but so is human liberty," another court explained (State v. Bartlett, 71 S.W. 148, 152 (Mo. 1902)).

One is as dear in the eye of the law as the other, and neither is to give way and surrender its legal status in order that the other may exclusively exist, supposing for a moment that such an anomaly to be possible. In other words, the wrongful and violent act of one man shall not abolish or even temporarily suspend the lawful and constitutional right of his neighbor. And this idea of the nonnecessity of retreating from any locality where one has the right to be is growing in favor, as all doctrines based upon sound reason inevitably will . . . . [No] man, because he is the physical inferior of another, from whatever cause such inferiority may arise, is, because of such inferiority, bound to submit to a public horsewhipping. We hold it a necessary self-defense to resist, resent, and prevent such humiliating indignity, — such a violation of the sacredness of one’s person, — and that, if nature has not provided the means for such resistance, art may; in short, a weapon may be used to effect the unavoidable necessity.

Yikes! Many jurists and commentators, particularly in the Northeast, found this reasoning repulsive.  “The ideal of the[] courts” that have propounded the “true man” doctrine, explained Harvard Law Professor Jospeph Beale in 1903 (Retreat from a Murderous Assault, 16 Harv. L. Rev. 567 (1903),

is found in the ethics of the duelist, the German officer, and the buccaneer. . . .  The feeling at the bottom of the [the rule] is one beyond all law; it is the feeling which is responsible for the duel, for war, for lynching; the feeling which leads a jury to acquit the slayer of his wife’s paramour; the feeling which would compel a true man to kill the ravisher of his daughter.  We have outlived dueling, and we deprecate war and lynching; but it is only because the advance of civilization and culture has led us to control our feelings by our will. . . A really honorable man, a man of truly refined and elevated feeling, would perhaps always regret the apparent cowardice of a retreat, but he would regret ten times more, after the excitement of the contest was past, the thought that he had the blood of a fellow-being on his hands.

This debate was realllllllly bitter and acrimonious.  I suppose the two sides disagreed about the impact of the “true man” doctrine on homicide rates. But obviously this conflict was a cultural one between groups—lets call them hierarchical individualists and egalitarian communitarians—both of which understood courts’ adoption or rejection of the “true man” doctrine as adjudicating the value of their opposing visions of virtue and the good society.

Well, along came the amazing super-liberal superhero Justice Holmes to save the day! In a 1921 decision called Brown v. United States, 256 U.S. 335, the U.S. Supreme Court had to figure out whether the federal self-defense standard—which like defenses generally was not codified in any statute—imposed a “duty to retreat.” Holmes concluded it didn’t. But his explanation why didn’t sound at all like what the Western and Southern “true man” courts—or anyone else—was saying in the “true man” controversy.

The law has grown, and even if historical mistakes have contributed to its growth it has tended in the direction of rules consistent with human nature. . . .  Detached reflection cannot be demanded in the presence of an uplifted knife.  Therefore in this Court, at least, it is not a condition of immunity that one in that situation should pause to consider whether a reasonable man might not think it possible to fly with safety or to disable his assailant rather than to kill him.

We can’t punish the poor bastard, Holmes was saying, not because he bravely defended his honor but because the circumstances reduced him to an unreasoning mass of blind impulse.  The “true man” doctrine had become the “scared shitless man”  doctrine!

WTF? Who had won? Who had lost?  It was the result the Hierarchical Individualists wanted but without the meaning that the Egalitarian Communitarians loathed.

Holmes had rendered this issue culturally meaningless--and therefore made disputing this one aspect of the law pointless for the dueling cultural factions.

And you know what the best thing is? Holmes did this on purpose!

The truth was, Holmes personally identified with the honor norms that animated the “true man” doctrine.  It resonated with his own pride over having been part of a Civil War regiment that “never ran.”  In his famous 1884 Memorial Day Address, Holmes spoke not of the thoughtless impulses of those who survived hand-to-hand combat, but rather of the “swift and cunning thinking on which once hung life or freedom.”

Writing of the issue in Brown to to his confidant Harold Laski, Holmes explained:

[L]aw must consider human nature and make some allowances for the fighting instinct at critical moments.  In Texas where this thing happened, . . . it is well settled, as you can imagine, that a man is not born to run away . . . .

Yet for Holmes the liberal jurist, the law decidedly was not not a place for civil war even when waged in the weaponry of partisan moralistic and largely symbolic language. Acknowledging how much less passionately he defended the no retreat rule in Brown, Holmes tells Laski, “I don’t say all I think in the opinion.”

Holmes's gambit worked.  The law stayed as it was. But because the “no retreat” principle no longer had any clear cultural resonance, people stopped fighting about it (and focused their attention elsewhere: e.g., on guns, and nuclear power, and climate change).

Until . . . the NRA, a tapeworm of cognitive illiberalism, got a brilliantly evil idea: Mount a campaign in Southern and Western states to get “stand your ground” laws passed!

Sure these new statutes wouldn’t actually change the law. But that wasn’t the point of them. 

The point was to reignite the cultural conflagration that Holmes had snuffed out. By enacting these laws, the NRA predictably provoked today’s egalitarian communitarians, who denounced the laws as certain to unleash a torrent of death and carnage.

That sort of response is really good for the NRA. It gets today’s hierarchical individualists very mad, which makes them give lots of money to the NRA to strike back against the insults that are being hurled upon them!

The sort of media coverage of the study that is the subject of this post is very welcome PR fodder for the NRA too. 

Sigh; where is our Holmes?

But . . . back to the paper!

I’d say the study’s mistaken premise – that the “law changed” in the “stand your ground” states—rises to the level of a serious flaw.  The authors didn’t measure what they thought they were measuring. The thing that their complexly structured statistical model says “caused” something—a change in law in 20 states--didn’t happen.

I’m not really sure, in all honesty, that this problem can be fixed. The commenter who brought the article to my attention wondered if maybe the authors could argue that even though the law didn’t change in so many of the “stand your ground” law states, the enactment of these symbolic laws put citizens who previously didn’t know the law on notice that they didn’t have to retreat and that’s what “explains” the homicide rate going up. 

Interesting, but I myself would feel queasy even attempting this sort of rescue mission here.  If one discovers that what one measured isn’t what one thought, it’s pretty dubious to invent a hypothesis that fits the result one nevertheless managed to find. That’s not materially different, in my view, from just poking around in data and concocting a story after the fact for whatever happened to be significant. But maybe that's just me.

Here’s another interesting thing, though.  While they might have forgotten (or simply never recognized) the heroic liberal statesmanship of Justice Holmes, lawyers, judges, law students and anyone else who had happened to pick up any basic text on criminal law knew that the “true man” doctrine was widespread—indeed, declared by many commentators and courts to be the “majority rule” in the U.S. Naturally, it occurred to scholars long before now to examine whether this position is linked to homicide rates in the (mainly) Southern & Western states that follow it.

The first-rate scholars Nisbett & Cohen wrote a great book, Culture of Honor: The Psychology of Violence in the South, that presented empirical evidence that the “no retreat” standard, along with other manifestations of cultural honor norms, were linked to high homicide rates in the South way back in 1996.

The authors’ very rough draft doesn’t mention Nisbett & Cohen either. If they tried to deal with this now, what would they say? That the “true man” doctrine made homicide rate higher than in “no retreat” sates, and yet the “stand your ground” laws made it go up higher still? Was there some dip in the middle? Perhaps betweeen1994 and 2000, people momentarily “forgot” what the law was in their states was, and were only reminded again by the new “Stand your ground” laws?...

But I myself think it is really not sensible to even try to make sense of results generated by a statistical model that rests on a mistaken factual premise.

Of course, these are matters for the authors to consider. I'm sure they are relieved they circulated their working paper so that they will now have an opportunity to think about these difficulties.


Brown, R.M. No Duty to Retreat: Violence and Values in American History and Society (1991).

Kahan, D.M. The Secret Ambition of Deterrence. Harv. L. Rev. 113, 413 (1999).

Kahan, D.M. & Nussbaum, M.C. Two Conceptions of Emotion in Criminal Law. Colum. L. Rev. 96, 269 (1996).

Nisbett, R.E. & Cohen, D. Culture of Honor: The Psyhcology of Violence in the South (1996).

White, G.E. Justice Oliver Wendell Holmes : law and the inner self. (Oxford University Press, New York; 1993).



Cultural vs. ideological extremists: the case of gun control

Look what those nut job socialists & libertarians are saying now: that if we really want to  reduce gun homicides—including the regular shooting of children on street corners in cities like Chicago—we should select one of the myriad sensible alternatives to our current "war on drugs," which predictably spawns violent competition to control a lucrative black market without doing much of anything to reduce either the supply or the demand for banned substances.

They just don’t get it!

So what if an expert consensus report from the National Academy of Sciences “found no credible evidence that the passage of right-to-carry laws decreases or increases violent crime.” Big deal that a Center for Disease Control task force “found insufficient evidence to determine the effectiveness of any of the firearms laws reviewed”—including waiting periods, ammunition bans, child access prevention laws, and “gun free school zones”—“for preventing violence.” 

Who cares that the best available evidence clearly suggests, in contrast, that there are myriad steps we could take (“wholesale legalization” vs. “wholesale criminalization” is a specious dichotomy) that would very appreciably reduce the number of homicides associated with the criminogenic property of our own drug-law enforcement policies?

The point isn’t to save lives! It’s to capture the expressive capital of the law.

Their role (real and fabled) in American history—in overthrowing tyranny and in perpetuating conditions of slavery and apartheid; in taming the frontier and in assassinating Presidents—have imbued guns with a rich surfeit of social meanings. Wholly apart, then, from the effect gun laws have (or don’t) on homicide, they convey messages that symbolically affirm and denigrate opposing cultural styles.

We are a liberal democratic society, comprising a plurality of diverse moral communities. The individual liberty provisions of our Constitution forbid the State to “enforce … on the whole society” standards of “private conduct” reflecting any one community’s “conceptions of right and acceptable behavior.”

So for crying out loud, how will we possibly be able to use State power to resolve whose way of life is virtuous and honorable and whose vicious and depraved if we don’t fixate on laws that have ambiguous public-welfare consequences but express unambiguously partisan cultural meanings?

What’s that? You say that the “war on drugs” should also be viewed as an exercise of expressive power aimed at enforcing a cultural orthodoxy?

Of course. But the partisan meanings that are expressed by those laws are ones that only “ideological extremists”—libertarians, socialists, et al.—would object to.


Center for Disease Control.First Reports Evaluating the Effectiveness of Strategies for Preventing Violence: Firearms Laws, Findings from the Task Force on Community Preventive Services (2003). 

Jacobs, J.B. Can gun control work? (Oxford University Press, Oxford ; New York; 2002).

Kahan, D.M.Cognitive Bias and the Constitution of the Liberal Republic of Science, working paper, available at

Kahan, D.M. The Cognitively Illiberal State. Stan. L. Rev. 60, 115-154 (2007).

Kahan, D.M. & Braman, D. More Statistics, Less Persuasion: A Cultural Theory of Gun-Risk Perceptions. U. Pa. L. Rev. 151, 1291-1327 (2003).

Kleiman, M. Marijuana : costs of abuse, costs of control. (Greenwood Press, New York; 1989).

Kleiman, M., Caulkins, J.P. & Hawken, A. Drugs and drug policy : what everyone needs to know. (Oxford University Press, Oxford ; New York; 2011).

MacCoun, R.J. & Reuter, P. Drug war heresies : learning from other vices, times, and places. (Cambridge University Press, Cambridge, U.K. ; New York; 2001).

Musto, D. F. (1987). The American Disease: Origins of Narcotic Control (Expanded ed.). New York: Oxford University Press.

National Research Council (U.S.). Committee to Improve Research Information and Data on Firearms., Wellford, C.F., Pepper, J., Petrie, C. & National Research Council (U.S.). Committee on Law and Justice. Firearms and violence : a critical review. (National Academies Press, Washington, DC; 2004). 




Are *positions* on the deterrent effect of the death penalty & gun control possible & justifiable? Of course!

So I started to answer one of the interesting comments in response to the last post & found myself convinced that the issues involved warranted their own post. So this one "supplements" & "adjusts" the last.

And by the way, I anticipate "supplementing" & "adjusting" everything I have ever said and ever will say.  If you don't see why that's the right attitude to have, then probably you aren't engaged in the same activity I am (which isn't to say that I plan to supplement & adjust every blog post w/ another; that's not the "activity" I mean to be involved in, but rather a symptom of something that perhaps I should worry about, and you too since you seem to be reading this).

Here's the question (from JB):

I'm puzzled about how the NRC dealt with Figure 2 in this paper, the "Canada graph" of Donohue and Wolfers. This is not multiple regression. (I agree that multiple regression is vastly over-used and that statistical control of the sort it attempts to do is much more difficult, if not impossible in many situations). But this graph settled the issue for me. It is not a regression analysis. . . .

Here's my answer:

@JB: The answer (to the question, what did NRC say about Fig. 2 in D&W) is . . . nothing  virtually nothing!

As you note, this is not the sort of multivariate regression analysis that the NRC's expert panel on the death penalty had in mind when it “recommend[ed] that these studies not be used to inform deliberations requiring judgments about the effect of death penalty on homicide.”

Your calling attention to this cool Figure furnishes me with an opportunity to supplement my post in a manner that (a) corrects a misimpression that it could easily have invited; and (b) makes a point that is just plain important, one I know you know but I want to be sure others who read my post do too.

The NRC reports are saying that a certain kind of analysis – the one that is afforded the highest level of respect by economists; that’s an issue that they really should talk about—is not valid in this context. In this context – deterrence of homicide by criminal law (whether gun control or capital punishment) --  these studies don’t give us any more or less reason to believe one thing or the other.

But that doesn’t mean that it is pointless to think about deterrence, or unjustifiable for us to have positions on it, when we are deliberating about criminal laws, including gun control & capital punishment! 

Two points:

First, just because one empirical method turns out to have a likelihood ratio of 1 doesn’t mean all forms of evidence have LR = 1!

You say, “hey, look at this simple comparison: our homicide rate & Candada’s are highly correlated notwithstanding how radically they differ in the use of the death penalty over time. That's pretty compelling!”

I think you would agree with me that that this evidence doesn’t literally “settle the issue.”  We know what people who would stand by their regression analyses (and others who merely wish those sorts of analyses could actually help) would say. Thinks like ... 

  • maybe the use of the death penalty is what kept the homicide rate in the US in “synch” with the Canadian one (i.e., w/o it, the U.S. rate would have accelerated relative to Canada, due to exogenous influences that differ in the 2 nations);
  • maybe when the death penalty isn’t or can’t be (b/c of constitutional probhition) used, legislators "make up the difference" by increasing the certainty of other, less severe punishments, and it is still the case that we can deter for "less" by adding capital punishment to the mix (after getting rid of all the cost-inflating, obstructionist litigation, of course);
  • maybe the death penalty work as James Fitzjames Stephen imagines – as a preference shaping device – and Canadians, b/c they watch so much U.S. TV are morally moulded by our culture (in effect, they are free riding on all our work to shape preferences through executing our citizens--outrageous);
  • variation in US homicide rates in response to the death penalty is too fine-grained to be picked  up by these data, which don’t rule out that the U.S. homicide rate would have decelerated in relation to Canada if the US had used capital punishment more frequently after Gregg;
  • the Donohue and Wolfers chart excludes hockey-related deaths resulting from player brawls and errant slapshots that careen lethally into the stands, and thus grossly understates the homicide rate in Canada (compare how few players and fans have been killed by baseball since Gregg!);
  • etc. etc. etc.   

These are perfectly legitimate points, I’d say. But what is the upshot?

They certainly don’t mean that evidence of the sort reflected in Fig. 2 is entitled to no weight – that its "Likelihood Ratio = 1."  If someone thinks that that’s how empirical proof works – that evidence either “proves” something “conclusively,” or “proves nothing, because it hasn’t ruled out all alternative explanations”—is “empirical-science illiterate” (we need a measure for this!).

These points just present us with reasons to understand why the data in Fig. 2 don't mean LR ≠ ε (if the hypothesis is “death penalty deter”; if hypothesis is “death penalty doesn’t,” then why LR ≠ ∞).

I agree with you that Fig 2 has a pretty healthy LR – say, 0.2, if the hypothesis is “the death penalty deters” – which is to say, that that I believe the correlation between U.S. and Canadian homicide rates is “5 times more consistent with” the alternative hypothesis (“doesn’t deter”).

And , of course, this way of talking is all just a stylized way of representing how to think about this—I’m using the statistical concept of “likelihood ratio” & Bayesianism as a heuristic. I have no idea what the LR really is, and I haven’t just multiplied my “priors” by it.

But I do have an idea (a conviction, in fact) about the sensible way to make sense of empirical evidence. It's that it should be evaluated not as "proving" things but as supplying more or less reason to believe one thing or another. So when one is presented with empirical evidence, one shouldn't say either "yes, game over!" or "pfffff ... what about this that & the other thing..." but rather should supplement & adjust what one believes, and how confidently, after reflecting on the evidence for a long enough time to truly understand why it supports a particular infernece and how strongly.

Second, even when we recognize that an empirical proposition relevant to a policy matter admits of competing, plausible  conjectures (they don't have to be “equally plausible”; only an idiot says that the “most plausible thing must be true!”), and that it would be really really nice to have more evidence w/ LR ≠ 1, we still have to do something.  And we can and should use our best judgment about what the truth is, informed by all the “valid” evidence (LR ≠ 1) we can lay our hands on.

I think people can have justifiable beliefs about the impact (or lack thereof) of gun control laws & the death penalty on homicide rates!

They just shouldn't abuse reason. 

They do that when they insist that bad statistical proofs -- simplistic ones ones that just toss out arbitrary bits of raw data; or arbitrarily complex yet grossly undertheorized ones like "y =b1*x1+ b2*x2 +b3*x3 ... +b75*x34^3 + ..." – “conclusively refute” or “demonstrably establish” blah blah blah.

And they do that and something even worse when they mischaracterize the best scientific evidence we do have.


A Tale of (the Tales Told About) Two Expert Consensus Reports: Death Penalty & Gun Control

What is the expert consensus on whether the death penalty deters murders—or instead increases them through a cultural “brutalization effect”?

What is the expert consensus on whether permitting citizens to carry concealed handguns in the public increases homicide—or instead decreases it by discouraging violent predation?

According to the National Research Council, the research arm of the National Academy of Sciences, the expert consensus answer to these two questions is the same:

It’s just not possible to say, one way or the other.

Last April (way back in 2012), an expert NRC panel charged with determining whether the “available evidence provide[s] a reasonable basis for drawing conclusions” about the impact of the death penalty

concluded that research to date on the effect of capital punishment on homicide is not informative about whether capital punishment decreases, increases, or has no effect on homicide rates. Therefore, the committee recommends that these studies not be used to inform deliberations requiring judgments about the effect of the death penalty on homicide. Consequently, claims that research demonstrates that capital punishment decreases or increases the homicide rate by a specified amount or has no effect on the homicide rate should not influence policy judgments.

Way way back in 2004 (surely new studies have come out since, right?), the expert panel assigned to assess the “strengths and limitations of the existing research and data on gun violence,”

found no credible evidence that the passage of right-to-carry laws decreases or increases violent crime, and there is almost no empirical evidence that the more than 80 prevention programs focused on gun-related violence have had any effect on children’s behavior, knowledge, attitudes, or beliefs about firearms. The committee found that the data available on these questions are too weak to support unambiguous conclusions or strong policy statements.

The expert panels’ determinations, moreover, were based not primarily on the volume of data available on these questions but rather on what both panels saw as limitations inherent in the methods that criminologists have relied on in analyzing this evidence. 

In both areas, this literature consists of multivariate regression models. As applied in this context, multivariate regression seeks to extract the causal impact of criminal laws by correlating differences in law with differences in crime rates “controlling for” the myriad other influences that could conceivably be contributing to variation in homicide across different places or within a single place over time. 

Inevitably, such analyses involve judgment calls. They are models that, like  many statistical models, must make use of imprecise indicators of unobserved and unobservable influences, the relationship of which to one another must be specified based on a theory that is itself independent of any evidence in the model.

The problem, for both the death penalty and concealed-carry law regression studies, is that results come out differently depending on how one constructs the models.

“The specification of the death penalty variables in the panel models varies widely across the research and has been the focus of much debate,” the NRC capital punishment panel observed. “The research has demonstrated that different death penalty sanction variables, and different specifications of these variables, lead to very different deterrence estimates—negative and positive, large and small, both statistically significant and not statistically significant."

That’s exactly the same problem that the panel charged with investigating concealed-carrry laws focused on:

The committee concludes that it is not possible to reach any scientifically supported conclusion because of (a) the sensitivity of the empirical results to seemingly minor changes in model specification, (b) a lack of robustness of the results to the inclusion of more recent years of data (during which there were many more law changes than in the earlier period), and (c) the statistical imprecision of the results.

This problem, both panels concluded, is intrinsic to the mode of analysis being employed. It can’t be cured with more data; it can only be made worse as one multiplies the number of choices that can be made about what to put in and what to leave out of the necessarily complex models that must be constructed to account for the interplay of all the potential influences involved.

“There is no empirical basis for choosing among these [model] specifications,” the NRC death penalty panel wrote.

[T]here has been heated debate among researchers about them.... This debate, however, is not based on clear and principled arguments as to why the probability timing that is used corresponds to the objective probability of execution, or, even more importantly, to criminal perceptions of that probability. Instead, researchers have constructed ad hoc measures of criminal perceptions. . . .

Even if the research and data collection initiatives discussed in this chapter are ultimately successful, research in both literatures share a common characteristic of invoking strong, often unverifiable, assumptions in order to provide point estimates of the effect of capital punishment on homicides.

The NRC gun panel said the same thing:

It is also the committee’s view that additional analysis along the lines of the current literature is unlikely to yield results that will persuasively demonstrate a causal link between right-to-carry laws and crime rates (unless substantial numbers of states were to adopt or repeal right-to-carry laws), because of the sensitivity of the results to model specification. Furthermore, the usefulness of future crime data for studying the effects of right-to-carry laws will decrease as the time elapsed since enactment of the laws increases. If further headway is to be made on this question, new analytical approaches and data sets will need to be used.

So to be sure, the NRC  reached its “no credible evidence" conclusion  on right-to-carry laws way back in 2004. But its conclusion was based on “the complex methodological problems inherent in” regression analysis--the same methodological problem that were the basis of the NRC’s 2012 conclusion that death penalty studies are "not informative" and "should not influence policy judgments."

Nothing's changed on that score. The experts at the National Academy of Sciences either are right or they are wrong to treat multivariate regression analysis as an invalid basis for inference about the effects of criminal law.

The reasoning here is all pretty basic, pretty simple, something that any educated, motivated person could figure out by sitting down with the reports for a few hours (& who wouldn't want to do that?!).

Yet all of this has clearly evaded the understanding of many extremely intelligent, extremely influential participants in our national political conversation.

I’ll pick on the New York Times, not because it is worse than anyone else but because it’s the newspaper I happen to read everyday.

Just the day before yesterday, it said this in an editorial about the NRC’s capital punishment report:

A distinguished committee of scholars convened by the National Research Council found that there is no useful evidence to determine if the death penalty deters serious crimes. Many first-rate scholars have tried to prove the theory of deterrence, but that research “is not informative about whether capital punishment increases, decreases, or has no effect on homicide rates,” the committee said.

Okay, that’s right. 

But here is what the Times’ editorial page editor said the week before last about concealed carry laws:

Of the many specious arguments against gun control, perhaps the most ridiculous is that what we really need is the opposite: more guns, in the hands of more people, in more places. If people were packing heat in the movies, at workplaces, in shopping malls and in schools, they could just pop up and shoot the assailant. . . . I see it differently: About the only thing more terrifying than a lone gunman firing into a classroom or a crowded movie theater is a half a dozen more gunmen leaping around firing their pistols at the killer, which is to say really at each other and every bystander. It’s a police officer’s nightmare. . . . While other advanced countries have imposed gun control laws, America has conducted a natural experiment in what happens when a society has as many guns as people. The results are in, and they’re not counterintuitive.

Wait a sec.... What about the NRC report? Didn’t it tell us that the “results are in” and that "it is not possible to reach any scientifically supported conclusionon whether concealed carry laws increase or decrease crime?

I know the New York Times is aware of the NRC’s expert consensus report on gun violence. It referred to the report in an editorial just a couple days earlier.

In that one, it called on Congress to enact a national law that would require the 35 states that now have permissive “shall issue” laws—ones that mandate officials approve the application of any person who doesn’t have a criminal record or history of mental illness—to “set higher standards for granting permits for concealed weapons.”  “Among the arguments advanced for these irresponsible statutes,” it observed,

is the claim that ‘shall issue’ laws have played a major role in reducing violent crime. But the National Research Council has thoroughly discredited this argument for analytical errors. In fact, the legal scholar John Donohue III and others have found that from 1977 to 2006, ‘shall issue’ laws increased aggravated assaults by “roughly 3 to 5 percent each year.


Yes, the NRC concluded that there was “no credible evidence” that concealed carry laws reduce crime.

But as I pointed out, what it said was that it “found no credible evidence that the passage of right-to-carry laws decreases or increases violent crime.” So why shouldn't we view the Report as also “thoroughly discrediting” the Times editorial’s conclusion that those laws“seem almost designed to encourage violence?”

And, yes, the NRC can be said (allowing for loose translation of more precise and measured language) to have found “analytical errors” in the studies that purported to show shall issue laws reduce crime. 

But those “analytical errors,” as I’ve pointed out, involve the use of multivariate regression analysis to try to figure out the impact of concealed carry laws. That’s precisely the sort of analysis used in the Donohue study that the Times identifies as finding shall issue laws increased violent crime. 

The “analytical errors” that the Times refers to are inherent in the use of multivariate regression analysis to try to understand the impact criminal laws on homicide rates. 

That’s why the NRC’s 2012 death penalty report said that findings based on this methodology are “not informative” and “should be ignored for policy analysis.”

The Times, as I said, got that point. But only when it was being made about studies that show the death penalty deters murder, and not when it was being made about studies that find concealed carry laws increase crime....

This post is not about concealed carry laws (my state has one; I wish it didn’t) or the death penalty (I think it is awful).

It is about the obligation of opinion leaders not to degrade the value of scientific evidence as a form of currency in our public deliberations.

In an experimental study, the CCP found that citizens of diverse cultural outlooks all believe that “scientific consensus” is consistent with the position that predominates within their group on climate change, concealed carry laws, and nuclear power.  Members of all groups were correct – 33% of the time.

How do ordinary people (ones like you & me, included) become so thoroughly confused about these things?

The answer, in part, is that they are putting their trust in authoritative sources of information—opinion leaders—who furnish them with a distorted, misleading picture of what the best available scientific evidence really is.

The Times, very appropriately, has published articles that attack the NRA for seeking to block federal funding of the scientific study of firearms and homicide.  Let’s not mince words: obstructing scientific investigation aimed at promoting society’s collective well-being is a crime in the Liberal Republic of Science.

But so is presenting an opportunistically distorted picture of what the state of that evidence really is.

The harm that such behavior causes, moreover, isn’t limited to the confusion that such a practice creates in people who (like me!) rely on opinion leaders to tell us what scientists really believe.

It includes as well the cynicism it breeds about whether claims about scientific consensus mean anything at all.  One day someone is bashing his or her opponents over the head for disputing or distorting “scientific consensus”—and the next day that same someone can be shown (incontrovertibly and easily) to be ignoring or distorting it too.

By the way, John Donohue is a great scholar, one of the greatest empirical analysts of public policy ever.

Both of the NRC expert consensus reports that I’ve cited conclude that studies he and other econometricians have done are “not informative” for policy because of what those reports view as insuperable methodological problems with multivariate analysis as a tool for understanding the impact of law on crime.

Donohue disagrees, and continues to write papers reanalyzing the data that the NRC (in its firearms study) said are inherently inconclusive because of "complex methodological problems" inherent in the statistical techniques that Donohue used, and continues to use, to analyze them.

But that’s okay.

You know what one calls a scientist who disputes “scientific consensus”?

A scientist.

But that’s for another day. 


Chewing the fat, so to speak...

I've already exhausted my allotted time for blogging in answering interesting comments related to the post on Silver's climate change wisdom. I invite others to weigh in (but not on whether Mann is a great climate scientist; see my post update on that).

In particular, I'd like help (Larry has provided a ton, but I'm greedy) on what is right/wrong/incisive/incomplete/provocative/troubling/paradoxical/inherently contradictory etc. about my statement, "Gaps between prediction and reality are not evidence of a deficiency in method. They are just evidence--information that is reprocessed as part of the method of generating increasingly precise and accurate probabilistic estimates." Also the questions of (a) how forecasting model imprecision or imperfection should affect policymaking proposals & even more interesting (given the orientation of this blog) (b) how to communicate or talk about this practical dilemma. (Contributions should be added to that comment thread.)

Two more things to think about, complements of Maggie Wittlin:

1. Who is afraid of obesity & why?  Maggie notes "new meta-analysis finds that overweight people (and, with less confidence, people with grade 1 obesity) have a lower risk of mortality than people with BMIs in the 'normal' range" and wonders, as do I, how cultural outlooks or other sources of motivated reasoning affect reactions to evidence like this -- or of the health consequences of obesity generally.

2. Forget terrorism; we're all going to die from an asteroid. Maggie also puts my anxiety about magnitude 7-8-9 terrorism into context by pointing out that the size/energy-releasing-potential of asteroid impacts on earth also follow a power-law distribution.  Given the impact (so to speak) of civilization-destroying asteroid collision, isn't preparing to protect earth from such a fate (however improbable) yet another thing that we need to do but are being distracted from doing by OHS's rules on removing shoes at airport security-screening stations?! I could do some research but Aaron Clauset's spontaneous & generous supply of references for the likelihood of "large" terrorism attacks makes me hope that some other generous person who knows the literature here will point us to useful sources.


Wisdom from Silver’s Signal & Noise, part 2: Climate change & the political perils of forecasting maturation

This is post 2 in my three part series on Silver’s Signal & Noise, which tied for first (with  Sharon Bertsch McGrayne’s The Theory That Would Not Die) in my “personal book of the year” contest (I’ve already mailed them both the quantity of gold bullion that I always award to the winner—I didn’t even divide it in half; or maybe I did, or possibly I even doubled or tripled it).

It turns out that Silver is not only amazingly good at statistical modeling & pretty decent at story telling. He also happens to be pretty wise (obviously this is a limited sample & I’ll update based on new information etc).

The nugget of wisdom I mined out of the book in the first post had to do with Silver’s idea that we should treat terrorist attacks a bit more like earthquakes.

This time I want to make a report on what Silver had to say about climate-change forecasting. One way to understand his assessment is that the practitioners of it are being punished for their methodological virtue. 

Silver essentially structures the book around prototypes. There’s baseball, which is to forecasting what Saudi Arabia is to oil drilling. There are elections, another data-rich field but one that gets screwed up by a combination of bad traits in those who prognosticate (they are full of themselves) and those who are consuming their prognostications (too many of them want to be told only what they want to hear).

And earthquakes—can’t be forecast, but can still yield lots of info.

And economics--a bastion of bad statistics hygiene.

Then there’s meteorology, which is the archetype prototype of forecasting excellence because it is super hard and yet has made measureable progress (that’s much higher praise than “immeasurable,” in this context) due to the purity and discipline of its practitioners. (I’m eager to see who gets to play Richard Loft, the director of Technology Development at NCAR in the upcoming movie adaptation of Signal; I’m guessing Pierce Brosnan, unless he is cast as Silver himself).

In Silver’s account, climate forecasting is traveling the path of meteorology. The problem is that emulating the meteorologists obliges climate forecasters to become unwitting manufacturers of the ammunition being directed against them in the political flack storm surrounding climate change.

One of the things that meteorology forecasters did that makes them the superheroes of Signal was calibration. They not only made prodigious predictions but then revisited and retooled their models in light of how close they came to their targets, thereby progressively improving their aim.

When climate forecasters do this—as they must—they leave themselves wide open to guerilla attack by those seeking to repel the advance of science. The reason is that error is an inevitable and indeed vitally productive element of the Bayesian-evolutionary process that characterizes the maturation of valid forecasting.

Gaps between prediction and reality are not evidence of a deficiency in method. They are just evidence, information that is reprocessed as part of the method of generating increasingly precise and accurate probabilistic estimates.

This is a subtle point to get across even if one is trying to help someone to actually understand how science works. But for those who are trying to confuse, the foreseeable generation of incorrect predictions furnishes a steady supply of resources with which to harass and embarrass and discredit earnest scientists.

Silver recounts this dilemma in explicating the plight of James Hansen, whose forecasts from 30 and 25 years were in many respects impressively good but just as importantly instructively wrong. Ditto for the IPCC’s 1990 predictions.

Another thing that the superhero meteorologists did right was, in effect, theorize. They enriched their data with scientific knowledge that enabled them to do things like create amazing simulations of the dynamics they were trying to make predictive sense of. As a result, they got a lot further than they would have if they had used brute statistical force alone.

Climate forecasters are doing this too, and as a result necessarily enlarging the target that they offer for political sniping.  The reason is that theory-informed modeling of dynamic systems is hard work, the payoffs of which are unlikely to accumulate steadily in a linear fashion but rather to accrue in incremental breakthroughs punctuated by periods of nothing.

Indeed, those who travel this path might well seem to be make slower progress at least temporarily than those who settle for simpler, undertheorized number-crunching strategies, which make fewer assumptions and thus expose themselves to fewer sources of error, which tend to compound within dynamic models. Silver notes, for example, that some of Hansen’s earlier predictions—which were in the nature of simple multivariate regressions—in some respects outperformed some of his subsequent, dynamic-simulation driven ones.

Again, then, the virtuous forecaster will, precisely as a result of being virtuous, find him- or herself vulnerable to opportunistic hectoring, particularly by anti-science, lawyerly critics who will adroitly collect and construct number-crunching models that generated more conservative predictions and thereby outperformed the more theoretically dynamic ones over particular periods of time (including ones defined by happenstance or design to capitalize on inevitable and inevitably noisy short-term fluctuations in things like global temperatures).

Silver mentions the work of Scott Armstrong, a serious forecaster who nevertheless confines himself to simple number-crunching and consciously eschews the sort of theory-driven enrichment that was the signature of meteorology’s advancement. “I actually try not to learn a lot about climate change,” Armstrong, who is famous for his “no change” forecast with respect to global temperatures, boasts. “I am a forecasting guy” (Signal, p. 403).

“This book advises you to be wary of forecasters who say that science is not very important to their jobs,” Silver writes, just as it advises us to be skeptical toward “scientists who say that forecasting is not important to their[s] . . . . What distinguishes science, and what makes a forecast scientific, is that it is concerned with the objective world. What makes forecasts fail is when our concern only extends as far as the method, maxim, or model” (p. 403).

For Silver, the basic reason to “believe” in—and be plenty concerned about—climate change is the basic scientific fact, disputed by no one of any seriousness, that increasing concentrations of atmospheric CO2 (also not doubted by anyone) conduce to increasing global temperatures, which in turn have a significant impact on the environment. Forecasting is less a test of that than a vital tool to help us understand the consequences of this fact, and to gauge the efficacy (including costs and benefits) of potential responses.

Seems right to me. Indeed, seems wise.

* * * *

Okay, here’s something else that I feel I ought to say.

One reason I was actually pretty excited to get to the climate forecasting chapter was to verify an extremely critical review of the book (issued well before the release date of it) by Michael Mann, climate scientist of “hockey stick” fame.

Frankly, I find the gap between Mann’s depiction and the reality of what Silver said disturbing. You’d get the impression from reading Mann’s review that Silver is a “Chicago School” “free market fundamentalist” who dogmatically attacks the assumptions and methods of climate forecasters.

Just not so. I’m mean really really really untrue.

Mann figures very briefly at the end of the chapter, where Silver reports Mann’s reaction to what is in fact the chapter's central theme—that climate forecasting is exposed to political perils precisely because those engaged in it are taking an uncompromisingly scientific approach.

Mann is obviously—understandably and justifiably!—frustrated and filled with anger.

He describes climate scientists themselves as being involved in a “street fight with these people”—i.e., the professional “skeptics” who hector and harass, distort and mislead (p. 409).

Of course, that’s a response that sees fighting as something climate scientists ought to be doing.

“It would be irresponsible for us as a community to not be speaking out,” Mann explains.

“Where you have to draw the line is to be very clear about where the uncertainties are,” he allows, but it would be a mistake to “have our statements so laden in uncertainty that no one even listens to what we’re saying.”

Silver doesn’t say this—indeed, had no reason to at the time he wrote the book—but I have to wonder whether Mann’s savage reaction to Silver is part of Mann’s “street fighting” posture, which apparently includes attacking even intellectually and emotionally sympathetic commentators whose excessive reflection on climate forecasting “uncertainty”  threatens to prevent the public from even “listen[ing] to what we’re saying.”

Mann is a great climate scientist. He is not a scientist of science communication.

For those who do study and reflect on science communication, whether simplifying things or dispensing with qualifications (not to mention outright effacing of complexity) will promote open-minded public engagement with climate science are matters characterized by uncertainties analogous to the ones that climate change forecasters deal with.

But I think one thing that admits of no uncertainty is that neither climate scientists nor scientists of science communication nor any other scientifically minded person should resort to simplification, effacement of complexity, and disregard for intellectual subtlety in describing the thoughtful reflections of a scholarly minded person who is trying to engage openly and candidly with complicated issues for the benefit of curious people.

That’s a moral issue, not an empirical one, and it goes to the nature of what the enterprise of scholarly discussion is all about.


Nature Climate Change study on science literacy & cultural polarization can now be downloaded from CCP site

We not only post "preprints" & "working papers, but also the published versions of our studies too so long as consistent with copyright & like agreements.

Nature journals ("mother Nature" plus its brood of baby Natures, such as Nature Climate Change, Nature Nanotechnology, Nature Biotechnolgy, and Nature Natural Law Review) usually permit authors to post in online repositories final versions of their published articles 6 mos. after they appear but only in a non-typeset form (you know, not a simple mimeograph or xerox of the article as it appeared in the journal).

Well, it is now possible to download a non-typeset version of the CCP study on science literacy (numeracy, too) & cultural polarization of perceived climate change risks.

Just click here!


Wisdom from Silver’s Signal & Noise, part 1: “Predicting” magnitude 7-8-9 terrorist attacks

So I finished Nate Silver’s Signal & the Noise a couple days ago.  I loved it! 

n fact, it managed, very unexpectedly, to sneak in as a late entrant and catch what looked like the sure winner for “my personal favorite book of the year,” Sharon Bertsch McGrayne’s The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy. The two ended up in a dead heat, I’d say  (super honorable mention to George Dyson’s Turing’s Cathedral & James Gleick’s The Information).

McGrayne is the better story teller. Silver's not bad in that regard but the reason he managed to score so high is that his book contains some genuine elements of wisdom. Or at least I thought so!

Over the course of three posts (I’m guessing), I’m going to feature three of the nuggets of insight that I spotted in the book.

The first has to do with the important parallels between earthquakes and terrorist attacks.

As likely everyone—whether or not they’ve read the book—knows, Signal is about the simultaneous indispensability and fallibility of data-driven forecasting. The book essentially uses certain cases as prototypes for what forecasting can and can’t do, when it does and doesn’t work, and why.

Baseball, e.g., works well because there are so much data and the outcomes of interest so straightforward.

Economic forecasting is absurdly bad, in large part because of the bad statistical hygiene of economists, who are theoretically dogmatic, enamored of post-hoc story-telling (they use a statistical tool for this: “overfitting”), and uninterested in iterative calibration of their models.

Another prototype is forecasting of earthquake occurrence.  Pretty much can’t be done: there aren’t enough events to form and test models; the underlying dynamics are likely chaotic—if not technically so, then practically, given the high number of interacting mechanisms; and measurement of those mechanisms is confined to exceedingly crude proxies.

But the kind of forecasting that can’t be done has to do with predicting the timing of earthquakes, particularly ones of significant magnitude.

What can be predicted, however, is the likely scale and frequency of earthquakes in particular locales.

The reason that can be done (and actually, one of the reasons that precise forecasting of timing probably can’t be) is that earthquake magnitude and frequency reflect a “power law” distribution.

In a power-law distribution, there will be a predictable incidence of extreme values—ones many more standard deviations from the mean than you’d ever expect to see in a normal, Gaussian or “bell-shaped” distribution. The classic illustration is height, which is normally distributed, vs. wealth, which reflects a power-law distribution: you’ll never find even one person 20 SDs taller than average (10.5', or so), whereas people who are 20 SDs wealthier than average (net worth of, oh, $2 billion,) or even 100 SDs ($10 billion, more or less), while not commonplace, definitely are out there (for this reason, it is not very meaningful to talk about "standard deviations" in wealth).

Well, if you have enough data to estimate the key parameters of a power law, you can form a reasonably precise estimate of the frequency of extreme values relative to more typical, more common-place ones.

One can do this for earthquakes, it turns out. The Gutenberg-Richter law characterizes the power-law distribution for earthquakes and makes it possible, based on the frequency of relatively “mild” earthquakes to conclude that San Francisco can be expected to have a “major” one (> 6.75 on Richter scale) once ever 30 years, whereas New York will have a major one on average, once every 12,000 years (Signal, p. 150).

This is useful information. It doesn’t tell you when you are likely to have a major earth quake. But it tells you that if you live in San Francisco you are an idiot not to plan for one, whereas if you live in New York, you’d likely be out of your mind to insist that every building be able to able to handle the same impact.

Okay, so Silver goes through all of this. But later in the book he uses this information to say something pretty insightful (to me!) about terrorism.

Terrorist incidents, Silver observes, reflect a power law distribution, too (pp. 430-31). From the number of relatively “small” incidents in a given locale, one can estimate, with a reasonable degree of precision, the expected frequency of progressively “larger” ones.

Could 9/11 have been “predicted”?  As to when & where—probably not (Silver hedges on this; I think he is guilty of a bit of hindsight bias). But as to whether? For sure.

Applying a power-law model with data compiled by Aaron Clauset, Silver concludes that, as of Sept. 10, 2001,  “a September 11-scale attack” could have been expected to occur on average “about once every eighty years in a NATO country” (p. 432), which (by my math) comes out to over a 10% chance in a given decade.

Updating the power-law estimate to incorporate this the new information associated with the occurrence of 9/11 itself, Silver reports that we now have reason to expect a 9/11-scale attack in a NATO country once every 40 years. That’s close to a 25% chance every decade (p. 432).

He also now estimates that there is a “10 percent chance of an attack that would kill at least 10,000 people in a NATO country,” a “3 percent change of an attack that would kill 100,000, and a 0.6 percent chance of one that would kill one million or more” in the next decade (p. 437).

The estimates, like any ones generated by Bayesian techniques, are provisional, and here are appropriately qualified in light of the relative spareness of the data and also various judgment calls about how to define the relevant class of events.

But the point is we know more with this information than we would without it.  Just as the Gutenberg-Richter law supplies information that can help determine the appropriate level of preparedness for earthquakes, this Clauset-Silver terrorism power law supplies us with information we can use to engage in more rational planning for terrorism.

There will (predictably) be many many many times more smaller terrorist incidents than “big” ones—just as there will be many many times more minor than major earthquakes.

But for both quakes as for terrorist attacks, the destructive energy of progressively “larger” ones increases exponentially relative to their diminishing frequency.

We might expect, say, 10 magnitude 6 quakes for every magnitude 7, but the magnitude 7 quake (according to Silver, pp. 437-38) releases 1,000x more energy than each of the 6’s and in the absence of appropriate preparation cause much more damage than all the 6’s combined.

Similarly, in NATO countries, there were scores of terrorist acts smaller than 9/11—a “magnitude 7” attack--in the three decades that led up to it, but the 9/11 death toll was higher than that for all of those combined (p. 438). 

If you have limited resources, it makes sense to invest them in the way that minimizes the expected harm by as great an amount as possible.

San Francisco should be devoting much more resources to bracing for the magnitude 7 quake than it does trying to prepare for the damage associated with the much more frequent but much less damaging smaller ones.

We devote a huge amount of resources to trying to deter or preempt small-scale attacks. Fine. But a blown up commuter-rail train or subway station will likely kill only a few dozen people, and even the downing of a commercial airliner only a few hundred. 

A “magnitude 8” or even “9”-- the release of a chemical or biological agent or the detonation of a nuclear device in an urban area--  has the potential to kill 10,000s or even 100,000s and, while much less likely seems well within the range of power-law range of possibility.

Certainly we should—and I’m sure are-- doing a lot to try to avert the latter sort of attack.  But trying to detect the precursors of such a thing—so that we can intervene and avert it—is very difficult; it is a lot like trying to predict when a magnitude 7 or 8 or 9 earthquake is going to occur.

Nevertheless, we should be preparing for a magnitude 7 or 8 or 9 terrorist attack, in the same way that we do prepare for magnitude 7 and above earthquakes in the places where they can be expected to occur. Cities like San Francisco mandate that structures be built to withstand major quakes and as a result only scores of people die in ones that kill 10,000s in countries like Iran and Armenia.

A civil preparedness capacity to respond to a magnitude 8 or 9 terrorist attack could likewise make a difference in orders of magnitude in the number of people killed by it.

We don’t have such a regime.  Relatively little of the money that the Department of Homeland Security has doled out since its inception have been used for large-scale crisis-response planning.  Moreover, major cities like Los Angeles and New York make what many would regard as only half-hearted efforts to prepare their emergency-response capacities, in part because things like mock evacuations and similar drills tend to be viewed as disruptive and also anxiety-provoking.

Instead, as Silver notes, the post-911 world is pervaded by various forms of “security theatre”— cumbersome screening procedures and goofy alert systems that gratify a public demand for action but are unlikely to contribute anything to public safety.

After the (completely inept) “underwear bomber” was foiled in Christmas 2009, President Obama responded to the media frenzy by upbraiding our intelligence services for “failing to connect the dots,” and “order[ed] an immediate effort to strengthen the criteria used to add individuals to our terrorist watchlists, especially the  ‘no-fly’ list”—a device that experts view as too bloated to be effective and as imposing needless burdens on travelers and security personnel alike.

A guy as smart as Obama doesn't actually need Nate Silver to tell him that you don’t try to improve your ability to pick up a signal by adding noise.

Rather, what he and the rest of us need is a science of science communication that would make as as smart about managing the political-psychology dynamics of risk perception as Silver is about data-driven forecasting.  If we lack the former, the substantial contribution the latter can make to securing the public welfare is wasted.


The black and white -- but mainly gray -- of gun control and drug prohibition, part 2

So ... this is actually part two of a two-part series on race, gun control, and drug criminalization.

Last time I went into the motivation behind the series. The more proximate cause was a question posed in the discussion of my post on legalizing drugs. 

The more remote—but more fundamental—was the unsettling sense I had upon reflecting on my feelings on the Newtown shooting.  The shooting upset me (as it did many, of course). But it upset me, too, to realize that I’m not that upset more or less continuously, because in fact young kids are being shot more or less continuously—not in elementary schools in communities like Newtown, but on street corners & playgrounds in cities like Chicago, Los Angeles and Detroit.

They are essentially part of the War on Drug’s “collateral damage.” And I guess in the same way we don’t worry overmuch about “collateral damage” in the form of deaths to civilians in our other wars, we don’t really get distracted by it here at home. . . .

However much progress one thinks can be made by laws restricting firearms, orders of magnitude more can be made by ending drug Prohibition, which like alcohol Prohibition combines opportunities for monopoly profits with the necessity for violent, extralegal enforcement of commercial obligations, creating a hyper-homicide cocktail potent enough to bend the historical curve of pacifism that is the signature of liberal markety societies.

There are some unconscious emotional dynamics at work here that ought to be exposed and critically examined. They include the partisan cultural meanings of recreational drugs that account for their being treated differently from alcohol.  They include, too, the predictably parochial nature of our empathic sensibilities, which lead us to attend selectively to forms of suffering and loss that are in fact universal in their nature and concentrated disproportionately on certain members of our society.

But as always, matters are complicated.

One of the complexities is the profound moral ambivalence that members of inner-city, largely minority communities themselves have toward drug criminalization.  That was the subject of the my last post, which described the powerful case that members of those communities often make for their entitlement to use the expressive power of the law as a countervailing force to oppose social influences—including commercial advertising of lawful products--that they believe unfairly diminish their power to instill in their children the dispositions, tastes, and habits that they (like all parents everywhere) perceive to be essential to their children’s’ prospects for living happy, flourishing lives.

Precisely because the impact of our policies on guns and drugs so profoundly and distinctively affect these communities, the power of their members to make law in a manner that relfects their judgments about the morally complicated, empirically uncertain issues involves necessarily goes straight to the core of their entitlement to enjoy meaningful self-government.

I don’t know what this element of the dilemma means for how political disputes over guns and over drugs should be resolved. If I said I did, I’d be contradicting myself (likely I already have in some place and in some way connected to this topic; only someone who doesn’t actually get the complexity involved will manage to get all the pieces to fit together in an analytically neat and tidy little pattern).  My point is just that this is an element of the dilemma that has to be taken into account; and for that reason, I want to take it into account by acknowledging that it complicates the argument I have been making about the mistaken overemphasis on regulating guns relative to deregulating drugs as a response to our Nation’s unacceptable gun-homicide rate. . . .

So, finally, some data (I’m sorry for going on; I should just accept that it is impossible ever to say enough and not keep trying).

It’s not a perfect measure of the ambivalence that the communities I’m describing feel, but what I’ve done, combining data from several CCP studies conducted over the last year, is break down attitudes on gun control and marijuana legalization by race. 

The sample consists of about 2500 individuals drawn from a nationally representative on-line sample of individuals recruited to participate in CCP studies of one sort or another.  I wanted to cobble together several data sets in order to get enough African-American sample to enable reasonably precise estimates; African-Americans make up 11% of the sample overall.

Start with this:

It shows that African Americans and whites in the sample held comparable attitudes overall toward marijuana legalization—about 60% support, actually—but were divided sharply on gun control, with African Americans decidedly more supportive. 

I’ve put Hispanics and Asians in, too, but realize that they (especially Asians) comprised an even smaller part of the sample, diminishing the precision of any estimate of the attitudes of these groups in the general population (the error bars are standard errors; double the interval, essentially, if you want 0.95 levels of confidence).  But we are on relatively solid ground for African Americans and whites.

Now to do a meaningful comparison of African American and whites, it is also useful to take account of ideology.  Support for gun control and for legalizing marijuana both are associated with being liberal (as that term is used in ordinary political discourse). African Americans are, on average, much more liberal than whites.  Can we see the racial difference, then, as reflecting the greater ideological diversity in the white population?

To answer that question, I think it is helpful to start by getting a sense of just how much more liberal African Americans are than whites.  Consider:

What I’ve done, essentially, is plot the distribution (with a kernel density estimate) of whites and African Americans respectively over a continuous measure of right-left political orientation formed by aggregating the subjects’ self-reported identification with the Democratic and Republican parties and their ideology on a “liberal-conservative” scale.

You can “see” how much more “liberal Democratic” African-Americans are. Whereas the mean score on the scale for whites puts them just shy of the middle of the “Liberal Democratic” scale, the mean for African-Americans is closer to +1 Standard Deviation toward “Liberal Democratic. Minus 1 SD in the distribution for African-Americans equates to being around the middle of the scale; minus 1 SD for whites is a little more than one SD toward "Conservative Republican." 

Basically, “normalizing” the scale for race, one would say that a “middle of the road” African American is as far right within his or her group as a “moderately conservative Republican” white is for his or hers. 

Now consider this:


These are “fitted values” based on regression analyses (click on the thumbnail if you'd like to see them) that treat race, “liberal Democratic” political orientation, and the interaction of those two as predictors for support for gun control and support for marijuana legalization, respectively.  They tell you, in effect, how a progressively more “liberal Democratic” orientation influences positions on these issues for both groups.  I’ve started plotting the African-American line at the middle of the “liberal Democratic” scale because the proportion of African Americans more “conservative Republican” than that is so small—and it is visually misleading, I think, to include them if one is trying to assess how important ideology is in explaining the difference in white & African-American views on drugs & on guns.

What you can see, in effect, is that African Americans are more supportive of gun control, and less supportive of marijuana legalization, than whites of comparable political outlook. 

The effect is most pronounced for marijuana legalization. There, political outlooks and race interact, signifying that the impact of becoming more liberal and Democratic on support for legalization is smaller for African Americans than for whites.  There is no similar interaction between political outlooks and race for gun control; in effect, African Americans are uniformly more pro-gun control than whites at any given point on the political outlook spectrum.

This was basically in line with what I expected. That is, based on what I know of the public opinion research, I expected African Americans to be more pro-gun control and less pro-legalization than whites, and in fact anticipated this effect would be more pronounced for marijuana legalization.

Still, I was surprised by the degree of support for legalization among African Americans generally.  The level of support is higher, I think, than it was in years past. And the differential between African Americans and whites—in relation to political outlooks--smaller than I expected.

I’ll have to ask Tracey Meares, who has studied this, whether I’m right in my recollection/expectation and what she thinks about these results (maybe I can even get her to offer her views on the blog!).

What does this add to the discussion of gun control and drug prohibition?


Information, too, that is only an imprecise indicator of what are in fact very very important differences in perspective, founded on differences in experience and cultural meaning, among citizens who need to deliberate on guns and drugs. 

You should try to learn as much as they can about the sources of these differences, and about the judgments of fact and value that underlie them.  If you don't do this, your positions on gun control and drug prohibition will not be well-considered, no matter what they are.




The black and white -- but mainly gray -- of gun control and drug prohibition, part 1

This is part one of a two-part series on race, gun control, and drug criminalization.

The motivation for the series grows out of discussion relating to my post on legalizing drugs (I’m simplifying; really, something like this) as a means of reducing the gun-homicide rate in the U.S.

A question was posed in the discussion about what African-American public opinion is on drugs and guns.  I’ve culled some data on that from past CCP studies.  I’ll present these data in the next post. In this one, I want to lay out some more background. . . .

One of the reasons I made the drug-legalization proposal was my sense of discomfort with the post-Newtown framing of the gun-homicide crisis in our country. There are (literally) orders of magnitude more children (adults too) being shot & killed in inner-city neighborhoods in cities like Chicago than are being shot & killed in mass shootings by mentally ill people. It’s unclear how effective gun control—of any sort—would be in reducing gun homicides of any type.  But it’s clear that a very large fraction of U.S. gun homicides (leaving out suicide, which accounts for more than half of U.S. gun deaths) are associated with the lethal violence incident to the black market status of recreational drugs like marijuana and cocaine.

Why the hell aren’t we talking about this? Why haven’t we been for years already, given the steady, relentless toll in death (not to mention ruined lives, wasted dollars, etc.) associated with our completely dysfunctional, idiotic drug-law regime?

Well, actually, some people do talk about our drugs laws—and in particular whether their should be legalization—quite a lot. Many of them live in the very areas where drug-related, including drug-law-related, violence is the highest.  And they aren’t—or certainly aren’t all—persuded that drug legalization is the way to go.

My brilliant colleague Tracey Meares first educated me on these issues back when we were both assistant professors (we had to clean the chalk boards after Richard Epstein’s & Cass Sunstein’s lectures; sometimes this kid from the neighborhood, Barack Obama, would help too) at the University of Chicago Law School.

She told me, and showed me with both research and with vivid examples from the neighborhoods right around us, that there was a profound ambivalence about drug criminalization in inner-city, largely African American communities in the South Side of Chicago. 

There was no ambivalence about the existing drug-law enforcement posture of both the state and federal governments: everyone recognized that basically disposing of the lives of people involved in the drug trade by just tossing them in jail for huge amounts of time was idiotic, as well as indescribably cruel both to them and their communities.

But it wasn’t at all the case that the citizens who were most adversely affected by this dumb policy all thought that drugs should be legal. On the contrary, most of them were deeply opposed to legalization on moral grounds. Moral not primarily in the illiberal sense of wanting to tell other adult people how to live their lives, but moral in the sense of wanting the same fair opportunity that all adults are entitled to have to mould the characters of their children, instilling in them the outlooks and dispositions and habits most conducive to their happiness and flourishing.

All parents compete in that shaping process, of course, with myriad other influences.  These include commercial, market-driven ones that try to conjure demand for useless or even pernicious products by inventing fanciful stories about the glamorous or virtuous ways of life they conduce to (think, as you might have been recently, about hideous  “man cards”; but think, too, of Virginia Slim, etc.).

Parents in the communities in the inner-city in the South Side of Chicago (at least in the early to mid-1990s, when I lived there) resented these forces, like all parents do. They hated the companies that plastered their communities with billboards and other forms of advertising targeted (they correctly perceived) at creating in their children a taste—emotional and physical—for products like “malt liquor” and cigarettes.

They worried that if recreational drugs were made legal, manufacturers of those products would join the ranks of commercial firms poisoning the moral environment in which they were raising their children.

The way they—or many of them; reasonable, reasoning citizens inevitably have differences of views on complex matters—tried to reconcile their support for drug criminalization with their opposition to the existing regime of drug-law-enforcement was by trying to reform the former. Organizing through the processes associated with the City’s innovative community policy program, they advocated things like “gang loitering” laws as alternatives to draconian criminal sentences.

I wasn’t sure that I agreed with all the positions members of these communities took on all these issues, particularly on the criminalziation of drugs (the gang-loitering law, in context, did seem quite sensible to  me).  

But one thing I did become convinced of was that they were better situated, in every relevant sense, to figure out how these various issues should be resolved in their lives than I was.  They hadn’t necessarily read the latest issue of the Journal of Criminal Law and Criminology but by seeking out information from people they trust, and employing their informed sense of who knows what about what, they had arrived –by the same means we all do, in all areas of our lives—at perfectly justifiable grounds for making complicated decisions.

Moreover, they were the ones whose lives those decisions, no matter who made them, were going to most meaningfully affect. They were the ones bearing all the relevant costs—in the form of the impact that whatever regime of laws and enforcement strategy would be adopted would have on their sons and daughters, their brothers and sisters, and nephews and nieces, and close friends and neighbors.

There’s no way to honor the dignity that reasoning people are due under these circumstances other than to respect their right to govern themselves.

... What were we talking about again?  Oh, drug laws and guns.

Another thing that people in these communities believed, very strongly, was that there should be significant regulation of guns.  Two weeks ago, the U.S. Court of Appeals for the Seventh Circuit told them that’s not an area in which they are entitled to govern themselves: relying on the U.S. Supreme Court’s recent Second Amendment decisions (including one, also involving Chicago, that reached the by-no-means obvious determination that the Second Amendment limits the power of state governments, and not merely that of the federal one) struck down an Illinois law that prohibits carrying a concealed handgun in public without a permit issued for “cause.”

I’m very doubtful that “tough gun laws”—which like prohibition of alcohol and drugs create black markets and the forms of violence that inevitably attend them—will contribute much to solving the problem of violent homicide in our country.  But I don’t have any doubt that people in places like Chicago have a right to figure that out for themselves.

Okay. . . Next time: some data.


Fung, A. Empowered participation : reinventing urban democracy. (Princeton University Press, Princeton, N.J.; 2004).

Kahan, D.M. & Meares, T.L. The Coming Crisis of Criminal Procedure. Geo. L.J. 86, 1153 (1998).

Meares, T.L. It's a Question of Connections. Val. U. L. Rev. 579 31, 579 (1997).

Meares, T.L. Social Organization and Drug Law Enforcement. Am. Crim. L. Rev. 35, 191 (1998).

Meares, T.L. & Kahan, D.M. Urgent times : policing and rights in inner-city communities. (Beacon Press, Boston; 1999).

Skogan, W.G. Police and community in Chicago : a tale of three cities. (Oxford University Press, Oxford ; New York; 2006).

Skogan, W.G. & Hartnett, S.M. Community Policing Chicago Style. (1997).


Gateway post ...

Hey, now that you are thinking about how consequential our mindless drug laws are for our unacceptable gun homicide rate, you should try the really good stuff ...


Catch up on commentary day

Lots of interesting comments on the "Less drug laws, less gun homicide" & "Mass opinion coherence & do psychologists tell more tall tales than political scientists?" posts, including some on latter from Stats Legend Andrew Gelman (who also responds w/ post at his own site).

Much more interesting than anything I had planned to say today -- plus I'd like to devote my own "blog time" today to re-reading & responding to them.


Do mass political opinions cohere? And do psychologists "generalize without evidence" more often than political scientists?

Stats Legend Andrew Gelman (whose blog everyone who enjoys being surprised and who values high-quality analytical thinking should read daily) has an interesting post on Steven Pinker.

Pinker asks “[w]hy, if you know a person’s position on gay marriage, can you predict that he or she will want to increase the military budget and decrease the tax rate,” a question he answers by observing that “[p]olitical philosophers have long known that the ideologies are rooted in different conceptions of human nature — a conflict of visions so fundamental as to align opinions on dozens of issues that would seem to have nothing in common.”

Gelman responds by (1) doing some quick GSS correlations, on the basis of which he concludes that “attitudes on such diverse issues are not so highly correlated”; and then (2) attributing Pinker’s error to Pinker’s being a psychologist rather than a political scientist and thus prone to “present[ing] ideas that are thought-provoking but . . . too general to quite work,” in contrast to political scientists who “take such ideas and try to adapt them more closely to particular circumstances.”

Some thoughts:

1. Pinker is clearly right to note that mass political opinions on seemingly diverse issues cohere, and Andrew, I think, is way too quick to challenge this.

I could cite to billions of interesting papers, but I’ll just show you what I mean instead. A recent CCP data collection involving a nationally representative on-line sample of 1750 subjects included a module that asked the subjects to indicate on a six-point scale “how strongly . . . you support or oppose” a collection of policies:  

  1. policy_gun  Stricter gun control laws in the United States.
  2. policy_healthcare  Universal health care.
  3. policy_taxcut  Raising income taxes for persons in the highest-income tax bracket.
  4. policy_affirmative action  Affirmative action for minorities.
  5. policy_warming  Stricter carbon emission standards to reduce global warming.


 Positions clustered on these “diverse” items big time. The average inter-item correlation was 0.66. The Cronbach’s alpha—a scale reliability measure based on item covariance and the number of items—was 0.91.

This is a degree of coherence that would  make any social scientist – psychologist or political scientist – beam. The highest possible alpha is 1.0, and anything above 0.70 is usually regarded as signifying a high degree of reliability.  Low reliability, measured in this way, is it’s own punishment, since it constrains the power of any sort of explanatory or predictive model involving the scale. With a score of 0.91 you can be confident that the power of your model won’t be dissipated by the noise associated with the imprecision of the observable "indicators" you are using to measure the latent variable. 

The latent variable being picked up by these policy items is obviously something akin to right-left political preferences, so let’s call the resulting measure “Liberal_policy.” (Additional items cohered better with each other than with these, forming a second "libertarian policy prefernce" scale; but let's keep things simple.)

Being able to form a scale like this with a general population sample is pretty good evidence in itself (and better than just picking two items out of GSS and seeing if they correlate) that people’s opinions on such matters cohere.

But just to make the case even stronger, let’s consider how much of the variance in liberal policy preferences can be explained by ideology. 

In the same data set, there was a five-point measure for self-described “liberal-conservative ideology” and a  seven-point one for identification with the two major political parties. Those two items were also highly correlated (r = 0.70), so I combined them into a scale (α = 0.82) coded to represent a right-wing ideological disposition, which I labeled “Conserv_repub.”

Regressing Liberal_policy on Conserv_repub, I discovered that the percentage of variance explained (R2) was 0.60. That’s high, as any competent psychologist or political scientist would tell you, and as I’m sure Andrew would agree!

Now Andrew noted that the degree of coherence in political preferences tends to be conditional on other characteristics, such as wealth, education, and political interest. Typically, political scientists use a “political knowledge” measure to assess how coherence in ideological positions vary.

I had a measure of that (a 9-item civics-test sort of thing) in the data set too. So I added it and a cross-product interaction term to my regression model. It bumped up the R2 – variance explained – by 4%, an increment that was statistically significant.  

Seems small, but how practically important is that? A commenter on Andrew’s blog noted that I tend to criticize fixating on R2 as an effect-size measure; my point, which is one that good social scientists—political scientists and psychologists! Andrew too!--have been making for decades is that R2 is not a good measure of the practical significance of an effect size, a matter that has to be determined by use of judgment with relation to the phenomenon at issue.

Well, to help us figure that out, I ran a Monte Carlo simulation to generate the predicted probability that a typical “Liberal Democrat” (-1 SD on Conserv_Repub) and a typical “Conservative Republican” (+1 SD) would support “stricter gun control laws” (seems topical; this is pre-Newtown, so it would be interesting to collect some data now to follow up), conditional on being “low” (-1 SD) or “high” (+1 SD) in political knowledge.

Seems (a) like variance in political knowledge (whatever its contribution to R2) can matter a lot – the probability that a high–political-knowledge Republican will oppose gun control is a lot lower than that for a low–political-knowledge one—but (b) there is still plenty of disagreement even among low–political-knowledge subjects. 

I’d say, then, that Andrew is being a bit too harsh on Pinker’s premise about political preference coherence.

2. Pinker is clearly wrong—not just in his answer but in his style of reasoning—to connect this sort of coherence to “different conceptions of human nature" among people of opposing ideologies

Pinker, however, is indeed doing something very objectionable: he is engaged in rank story-telling

He notes that political philosophers identify ideologies with different conceptions of “human nature,” a “conflict of visions so fundamental as to align opinions on dozens of issues.” Well, maybe political philosophers do do that. But the idea that “different conceptions of ‘human nature’ ” explain coherence and variance in mass political opinion is an empirical claim, and as far as I know there’s not any support for it. 

I think it’s almost certainly false. Measures of ideology of the sort that I have used here have not – as far as I know; please do tell me if I’m wrong: the pleasure of learning something new will more than compensate me for the embarrassment of being shown to be ignorant -- been validated as predictors of “different conceptions of human nature.” Indeed, I think the idea that ordinary members of the public have “conceptions of human nature” is extravagant—the sort of thing only someone who has never ventured outside a university campus would likely believe.

There are myriad theories about the puzzling question of how ordinary people, who really aren’t philosophers, aren’t that interested in politics, and who are very consumed with other things can manage to form coherent ideological preferences. And they’ve been tested empirically.

It’s irritating for anyone who is familiar with all that work to see Pinker advance the sort of claim he does—which he presents not even as a conjecture but as a simple, unqualified, fact-of-the matter report.

3. Pinker’s mistake is one psychologists would resent as much as political scientists.

The sort of thing Pinker is doing here generalizes.  Popular commentators love to reach into the grab bag of decision science mechanisms and construct just-so stories that purport to “explain” complicated phenomena (e.g., political controversy over climate change). 

Good social scientists hate this.  Indeed, Pinker generally doesn’t like it, in fact; he complains about this practice in his excellent book, The Better Angels of Our Nature: Why Violence Has Declined, which admirably tries to connect trends in violence over history to mechanisms that themselves have support in evidence. I find it sort of deflating to see that he seems to adopt a different approach in the writing he does for the New York Times.

But the point is, resentment of story-telling is something that psychologists and political scientists would both experience. It’s not a consequence of Pinker being a psychologist!

4. Ironically, Andrew is making the sort of mistake he says Pinker made.

This last point follows from all the others. Andrew sees Pinker doing something irritating, and then treats a conjecture (I think a pretty uninteresting, implausible one; but all conjectures are created equal – test away!) as a general law that explains this particular instance, etc.

But now I will offer a conjecture, based on an observation-grounded theory.

The observation-grounded theory is that Andrew Gelman has a virtuous Bayesian disposition. That is, he is the sort of person who very happily updates and revises his views, which he always regards as just provisional estimates anyway.

The conjecture: that Andrew, on reflection, will agree that he offered a poor diagnosis (“psychologists generalize without evidence, unlike political scientists, who look for concrete evidence in particulars!”) of Pinker’s objectionable style of argumentation here (which, again, strikes me as uncharacteristic of Pinker himself!).

And now, let’s collect some evidence.

(One more prediction, or hope: Andrew will like my graphic!)

p.s. Ideological coherence in policy prefernces isn't nearly as interesting -- nearly as surprising, puzzling --as ideological or cultural coherence in factual beliefs (e.g., "earth is/is not heating up" & "children of gay & lesbians do worse/no worse in life than ones raised by heterosexual parents." That's what CCP research is all about. Perhaps I'll do another post on that.


Abelson, R.P. A Variance Explanation Paradox: When a Little is a Lot. Psychological Bulletin 97, 129-133 (1985).

Delli Carpini, M.X. & Keeter, S. What Americans Know About Politics and Why It Matters. (Yale University Press, New Haven; 1996).

Gelman, A. & Hill, J. Data Analysis Using Regression and Multilevel/Hierarchical Models. (Cambridge University Press, Cambridge ; New York; 2007).

John, O.P. & Benet-Martínez, V. in Handbook of research methods in social and personality psychology. (eds. H.T. Reis & C.M. Judd) 339-369 (Cambridge University Press, New York; 2000).

King, G. How Not to Lie with Statistics. Am. J. Pol. Sci. 30, 666-687 (1986). 

King, G., Tomz, M. & Wittenberg., J. Making the Most of Statistical Analyses: Improving Interpretation and Presentation. Am. J. Pol. Sci 44, 347-361 (2000).

Pinker, S. The better angels of our nature : why violence has declined. (Viking, New York; 2011).


Actually, empirical evidence suggests a sure fire way to dramatically lower gun homicides: repeal drug laws

Sticking my umbrella up to try to deflect the tsunami of specious, beside-the-point, hiding-the-cultural-imperialism-ball, insult-to-reason uses of empirical evidence on violence & gun control (emanating from those on both sides of the debate), I offered a couple of feeble blog posts (here and here) urging more thoughtful, grounded arguments that are mindful both of the limits of our knowledge and our duty, as citizens of a liberal democracy, to justify our policy positions on grounds free of the impulse to use law as an expressive weapon for denigrating cultural styles that differ from our own.

I'm not satisfied by my performance.

The problem isn't that what I wrote will make no difference, have no effect, etc. If that were the decisive issue, why would I ever say anything? I'm not trying to change the world; I'm just trying to engage other curious and concerned citizens who also want to think about issues reflectively and form positions that they think are factually supportable and morally defensible. I'm trying to help them so they'll help me back, since I'm by no means certain I'm right either.

No, the problem wasn't the futility of what I said but the incompleteness. "Don't look to statistics" -- could be read as denigrating the utility of empirical inquiry in assessing public policy and as expressing a sort of nihilistic "who cares, nothing we can do!" attitude, both of which would deeply misrepresent how I feel about evidence-based policymaking generally & about using evidence to think about guns.

So to amend I will emend.  

I now want to point out that in fact, while the empirical evidence on the relationship between gun control and homicide is (at this time at least) utterly inconclusive, there certainly are policies out there that we have very solid evidence to believe would reduce gun-related homicides very substantially.

The one at the top of the list, in my view, is to legalize recreational drugs such as marijuana and cocaine.

The theory behind this policy prescription is that illegal markets breed competition-driven violence among suppliers by offering the prospect of monopoly profits and by denying them lawful means for enforcing commercial obligations.

The evidence is ample. In addition to empirical studies of drug-law enforcement and crime rates, it includes the marked increase in homicide rates that attended alcohol prohibition and the subsequent, dramatic deline of it after repeal of the 18th Amendment.

from Claude Fischer, Berkeley Blog Actually, it's pretty interesting to look at homicide rates over a broader historical time frame than typically is brought into view by those who opportunistically crop the picture in one way or another to support their position for or against gun control.  What you see is that there is a pretty steady historical trend toward decline in the US punctuated by expected noisy interludes but also by what appear to be some genuine, and genuinely dramatic, jumps & declines.

One of the jumps appears to have occurred with the onset of prohibition and one of the declines with repeal of prohibition.  Social scientists doing their best to understand the evidence generally have concluded that that those are real shifts, and that they really were caused by prohibition and repeal.  

from Claude Fischer, Berkeley Blog

Criminologists looking at the impact of drug prohibition can use the models developed in connection with alcohol prohibition and other modeling strategies to try to assess the impact of drug prohibition on crime. Obviously the evidence needs to be interpreted, supports reasonable competing interpretations, and can never do more than justify provisional conclusions, ones  that are necessarily subject to revision in light of new evidence, new analyses, and so forth.

But I'd say the weight of the evidence pretty convincingly shows that drug-related homicides generated as a consequence of drug prohibition are tremendously high and account for much of the difference in the homicide rates in the U.S. and those in comparable liberal market societies (the non-liberal, non-market societies all are burdened with homicide rates orders of magnitude higher; guns don't explain that--  the pacifying influence of doux commerce does).  By all means decide for yourself, though; I've cited some reading material at the end of this post & urge others to call our attention to more in the comments section.

There are obviously other spikes & dips in the "secular" (as econometricians would say; here that's a very nice adjective to use) downward trend in homicide in the U.S. E.g., the upsurge of homicides in the 1960s and the decline in the 1990s. Most of the gun-control combatants mine this period for support for their claims -- they should, since the data are rich with support for specious inference.  Scholarly discussion here recognizes that the evidence on the contribution of guns to these jumps is utterly, hopelessly inconclusive.

There is a very interesting empirical study, though, by economist Jeffrey Miron, who concludes that the available evidence is consistent with the hypothesis that the difference in homicide rates in the US and in other liberal market societies is attributable to our drug prohibition policies. Gun availability in the US, according to this hypothesis, doesn't directly account for the difference in homicide rates between the US and these countries; rather, gun availability mediates the impact between drug prohibition and homicide rates in the US, because the criminogenic properties of drug prohibition create both a demand for murder of one's competitors and a demand for guns to use for that purpose.  

One of the very nice things about Miron's analysis, too, is that he is appropriately provisional about his conclusions:  

The empirical results presented above provide a possible explanation for the large differences in violence rates across countries, and they suggest that previous analyses might have spuriously attributed these differences to gun control or availability. According to the analysis here, differences in drug prohibition enforcement explain differences in violence, which in turn explain differences in gun ownership that correlate positively with violence but do not cause that violence. Further, the results provide a hint that restrictive gun control regimes can themselves increase violence. As noted above, these results should be considered suggestive rather than conclusive. Future research on these issues will need to exploit time‐series rather than cross‐sectional data.

 That's what a real scholar sounds like, you see. In my view, it's what an open-minded citizen sounds like too.

Now one thing to note: Obviously, decriminalizing marijuana and cocaine couldn't be expected to prevent mass shootings like the one in Newtown, or Aurora, or Phoenix, or Columbine, etc. (Maybe there'd be fewer guns around, actually, if we didn't have the demand for them associated with their contribution to the illegal drug trade, but there are already so many around -- the gun & people populations are neck-and-neck -- that I think disturbed people would still have no trouble getting their hands on them.)

But here's another thing to note: these very sad incidents "represent only a sliver of America's overall gun violence." Those who are appropriately interested in reducing gun homicides generally and who are (also appropriately) making this tragedy the occasion to discuss how we as a society can and must do more to make our citizens safe, and who are, in the course of making their arguments invoking (appropraitely!) the overall gun homicide rate should be focusing on what we can be done most directly and feasibly to save the most lives.

Repealing drug laws would do more --  much, much, much more -- than banning assault rifles (a measure I would agree is quite appropriate); barring carrying of concealed handguns in public  (I'd vote for that in my state, if after hearing from people who felt differently from me, I could give an account of my position that fairly meets their points and doesn't trade on tacit hostility toward or mere incomprehension of  whatever contribution owning a gun makes to their experience of a meaningful free life); closing the "gun show" loophole; extending waiting periods etc.  Or at least there is evidence for believing that, and we are entitled to make policy on the best understanding we can form of how the world works so long as we are open to new evidence and aren't otherwise interfering with liberties that we ought, in a liberal society, to respect.

...Now, what other policies might help? And in particular, if we are concerned about deaths of children?   Well, there's swimming pools .... But I've said enough for now.


Barnett, R. & Trip, B. Drug Prohibition and the Weakness of Public Policy’(1994). Yale LJ 103, 2593. 

Husak, D. Legalize This! The Case for Decriminalizing Drugs. (Verso, New York; 2002).

Jensen, G.F. Prohibition, Alcohol, and Murder Untangling Countervailing Mechanisms. Homicide Studies 4, 18-36 (2000).

Kleiman, M. Marijuana : costs of abuse, costs of control. (Greenwood Press, New York; 1989).

Kleiman, M., Caulkins, J.P. & Hawken, A. Drugs and drug policy : what everyone needs to know. (Oxford University Press, Oxford ; New York; 2011).

MacCoun, R.J. & Reuter, P. Drug war heresies : learning from other vices, times, and places. (Cambridge University Press, Cambridge, U.K. ; New York; 2001).

Miron, J.A. & Zwiebel, J. The Economic Case Against Drug Prohibition. The Journal of Economic Perspectives 9, 175-192 (1995).

Miron, J.A. Violence, Guns, and Drugs: A Cross‐Country Analysis*. Journal of Law and Economics 44, 615-633 (2001).

 Pinker, S. The better angels of our nature : why violence has declined. (Viking, New York; 2011).