Cultural Cognition Blog, 31 May 2016 14:14:13 +0000en-USSquarespace V5 Site Server v5.13.395-168 ("According to climate scientists ..." -- WTF?! (presentation summary, slides)Dan KahanTue, 31 May 2016 13:12:21 +0000 talk saturday at the annual Association for Psychological Science on Sat.  Was on a panel that featured great presentations by Leaf Van Boven, Rick Larrick & Ed O'Brien. Maybe I'll be able to induce them to do short guest posts on their presentations, although understandably, they might be shy about become instant world-wide celebrities by introducing their work to this sites 14 bilion readers.

Anyway, my talk was on the perplexing, paradoxical effect of "according to climate scientists" or ACS prefix (slides here).

As 6 billion of the readers of this blog know-- the other 8 have by now forgotten b/c of all the other cool things that have been featured on the blog since the last time I mentioned this--attributing positions on the contribution of human beings to global warming, and the consequences thereof, to "climate scientists" magically dispels polarization on responses to cliimate science literacy questions.

Here's what happens when "test takers" (members of a large, nationally representative sample) respond to two such items that lack the magic ACS prefix:

Compare what happens with the ACS prefix:

Does this make sense?

Sure: Questions that solicit respondents’ understanding of what scientists believe about the causes and consequences of human-caused global warming avoid forcing individuals to choose between answers that reveal what they know about what science knows, on the one hand, and ones that express who they are as members of cultural groups, on the other.

Here's a cool ACS prefix corollary:

Notice that the "Nuclear power" question was a lot "harder" than the "Flooding" one once the ACS prefix nuked (as it were) the identity-knowledge confound.  Not surprisingly, only respondents who scored the highest on the Ordinary Science Intelligence assessment were likely to get it right.

But notice too that those same respondents--the ones highest in OSI--were also the most likely to furnish the incorrect identity-expressive responses when the ACS prefix was removed.

Of course! They are the best at supplying both identity-expressive and  science-knowledge-revealing answers.  Which one they supply depends on what they are doing: revealing what they know or being who they are.

The ACS prefix is the switch that determines which of those things they use their reason for.

Okay but what about this: do rspts of opposing political ordinations agree on whether climate scientists agree on whether human-caused climate change is happening?

Of course not!

In modern liberal democratic societies, holding beliefs contrary to the best available scientific evidence is universally understood to be a sign of stupidity. The cultural cogniton of scientific consensus describes the psychic pressure that members of all cultural groups experience, then, to form and persist in the belief that their group’s position on a culturally contested issue is consistent with the best avaialbel scientific evidence.

But that's what creates the "WTF moment"-- also known as a "paradox":

Um ... I dunno!

That's what I asked the participants--my fellow panelists and the audience members (there were only about 50,000 people, because were scheduled against some other pretty cool panels) to help me figure out!

They had lots of good conjectures.

How about you?

"Repugnance" & reasoned deciscionmaking ... a fragmentDan KahanWed, 25 May 2016 11:11:00 +0000 something I working on ...

Disgust-motivated cognition of costs and benefits

 “Repugnance” can figure in an agent’s instrumental reasoning in a number of ways. One would be as an argument in his or her utility function: repugnant states of affairs are ones worth incurring a cost to avoid; the repugnance of an act is a cost that must be balanced against the value of the otherwise desirable states of affairs that the action might help to promote (e.g., Becker 2013). Alternatively, repugnance might be viewed as investing acts or states of affairs with some “taboo” quality that makes them inappropriate objects of cost-benefit calculation (Fiske & Tetlock 1997). I will address a third possibility: that repugnance might unconsciously shape how actors appraise consequences of actions or states of affairs.  Wholly apart from whatever disutility an agent might assign an act or state of affairs on account of its being repugnant, an agent is likely to conform his or her assessment of information about its risks and benefits to the aversion that it excites in her (Finucane, Alhakami, Slovic & Johnson 2000; Douglas 1966). I will survey the psychological mechanisms for this form of “disgust-motivated” reasoning and assess its implications for rational decisionmaking, individual and collective.

Becker, G.S. The economic approach to human behavior (University of Chicago press, 2013).

Finucane, M.L., Alhakami, A., Slovic, P. & Johnson, S.M. The Affect Heuristic in Judgments of Risks and Benefits. Journal of Behavioral Decision Making 13, 1-17 (2000).

Fiske, A.P. & Tetlock, P.E. Taboo Trade-offs: Reactions to Transactions That Transgress the Spheres of Justice. Political Psychology 18, 255-297 (1997).

Can you spot which "study" result supports the "gateway belief model" and which doesn't? Not if you use a misspecified structural equation model . . .Dan KahanFri, 20 May 2016 14:08:37 +0000 promised “yesterday”: a statistical simulation of the defect in the path analysis that van der Linden, Leiserowitz, Feinberg & Maibach (2015) present to support their “gateway belief model.”

VLFM report finding that a consensus message “increased” experiment subjects’ “key beliefs about climate change” and “in turn” their “support for public action” to mitigate it. In support of this claim, they present this structural equation model analysis of their study results:

As explained in my paper reanalyzing their results, VLFM’s data don’t support their claims. They nowhere compare the responses of subjects “treated” with a consensus message and those furnished only a “placebo” news story on a Star Wars cartoon series.  In fact, there was no statistically or practically significant difference in the “before and after” responses of these two groups of subjects’ expressions of belief in climate change or support for global warming mitigation.

The VLFM structural equation model obscures this result.  The model is misspecified (or less technically, really messed up) because it contains no variables for examining the impact of the experimental treatment—exposure to a consensus message—on any study outcome variable besides subjects’ estimates of the percentage of climate scientists who adhere to the consensus position on human-caused global warming.

To illustrate how this misspecification masked the failure of the VLFM data to support their announced conclusions, I simulated two studies designed in the same way as VLFM’s. They generated these SEMs:

As can be seen, all the path parameters in the SEMs are positive and significant—just as was true in the VLFM path analysis.  That was the basis of VLFM’s announced conclusion that “all [their] stated hypotheses were confirmed.”

"Study No. 1" -- is this the one that supports the "gateway model"?But by design, only one of the simulated study results supports the VLFM hypotheses.  The other does not; the consensus message changes the subjects’ estimates of the percentage of scientists who subscribe to the consensus position on human-caused climate change, but doesn’t significantly affect (statistically or practically) their beliefs in climate change or support for mitigation--the same thing that happened in the actual VLFM study.

The path analysis presented in the VLFM paper can’t tell which is which.

Can you?  If you want to try, you can download the simulated data sets here.

To get the right answer, one has to examine whether the experimental treatment affected the study outcome variable (“mitigation”) and the posited mediators (“belief” and  “gwrisk”) (Muller, Judd & Yzerbyt 2005). That’s what VLFM’s path analysis neglects to do.  It’s the defect in VLFM that my re-analysis remedies.

Or is it "Study No. 2"? Download the data & see; it's not hard to figure out if you don't use a misspecified SEMFor details, check out the “appendix” added to the VLFM data reanalysis

Have fun—and think critically when you read empirical studies.

Muller, D., Judd, C.M. & Yzerbyt, V.Y. When moderation is mediated and mediation is moderated. Journal of personality and social psychology 89, 852 (2005).

van der Linden SL, Leiserowitz A.A., Feinberg G.D., Maibach E.W. The Scientific Consensus on Climate Change as a Gateway Belief: Experimental Evidence. PLoS ONE (2015), 10(2): e0118489.doi:10.1371/journal.pone.0118489.

Serious problems with "the strongest evidence to date" on consensus messaging ...Dan KahanThu, 19 May 2016 08:10:00 +0000 . . .

van der Linden, Leiserowitz, Feinberg & Maibach (2015) posted the data from their study purporting to show that subjects exposed to a scientific-consensus message “increased” their “key beliefs about climate change” and “in turn” their “support for public action” to mitigate it.

Christening this dynamic the "gateway belief" model, VLFM touted their results as  “the strongest evidence to date” that “consensus messaging”— social-marketing campaigns that communicate scientific consensus on human-caused global warming—“is consequential.”

At the time they published the paper, I was critical because of the opacity of the paper’s discussion of its methods and the sparseness of the reporting of its results, which in any case seemed underwhelming—not nearly strong enough to support the strength of the inferences the authors were drawing.

But it turns out the paper has problems much more fundamental than that.

I reanalyzed the data, which VLFM posted in March, a little over a year after publication,  in conformity with the “open data” policy of PLOS ONE, the journal in which the article appeared.

As I describe in my reanalysis, VLFM fail to report key study data necessary to evaluate their study hypotheses and announced conclusions.

Their experiment involved measuring the "before-and-after" responses of subjects who received a “consensus message”—one that advised them that “97% of climate scientists have concluded that human-caused climate change is happening”—and those who read only “distractor” news stories on things like a forthcoming animated Star Wars cartoon series.

In such a design, one compares the “before-after” response of the “treated” group to the “control,” to determine if the "treatment"—here the consensus message—had an effect that differed significantly from the control placebo. Indeed, VLFM explicitly state that their analyses “compared” the response of the consensus-message and control-group subjects

But it turns out that the only comparison VLFM made was between the groups' respective estimates of the percentage of climate-change scientists who subscribe to the consensus position. Subjects who read a statement that "97% of climate scientists have concluded that climate-change is happening" increased theirs more than did subjects who viewed only a distractor news story.

But remarkably VLFM nowhere report comparisons of the two groups' post-message responses to items measuring any of the beliefs and attitudes for which they conclude perceived scientific consensus as a critical "gateway" .

Readers including myself, initially, thought that such comparisons were being reported in a table of “differences” in “Pre-” and “Post-test Means” included in the article.

These aren't experimental effects after all...

But when I analyzed the VLFM data, I realized that, with the exception of the difference in "estimated scientific consensus," all the "pre-" and "post-test" means in the table had combined the responses of consensus-message and control-group subjects.

There was no comparison of the pre- and post-message responses of the two group of subjects; no analysis of whether their responses differed--the key information necessary to assess the impact of being exposed to a consensus message.

Part of what made this even harder to discern is that VLFM presented a complicated “path diagram” that can be read to imply that exposure to a consensus message initiated a "cascade" (their words) of differences in before-and-after responses, ultimately leading to “increased support for public action”—their announced conclusion.

The misspecified "gateway belief" SEM...

But this model also doesn't compare the responses of consensus-message and control-group subjects on any study measure except the one soliciting their estimates of the "percentage of scientists [who] have concluded that human-caused climate change is happening."

That variable is the only one connected by an arrow to the "treatment"--exposure to a consensus message.

As I explain in the paper, none of the other paths in the model distinguishes between the responses of subjects “treated” with a consensus message and those who got the "placebo" distractor news story. Accordingly, the "significant" coefficients in the path diagram reflect nothing more than correlations between variables one would expect to be highly correlated given the coherence of people’s beliefs and attitudes on climate change generally.

In the paper, I report the data necessary to genuinely compare the responses of the consensus-message and control-group subjects.

It turns out that, subjects exposed to a consensus message didn’t change their “belief in climate change” or their “support for public action to mitigate it” to an extent that significantly differed, statistically or practically, from the extent to which control subjects changed theirs.

Indeed, the modal and median effects of being exposed to the consensus message on the 101-point scales used by VLFM to measure "belief in climate change" and "support for action" to mitigate it were both zero--i.e., no difference in "after" or "before" responses to these  study measures.

No one could have discerned that from the paper either, because VLFM didn't furnish any information on what the raw data looked like. In fact, both the consensus-message and placebo news-story subjects' '"before-message" responses were highly skewed in the direction of belief in climate change and support for action, suggesting something was seriously amiss with the sample, the measures, or both--all the more reason to give little weight to the the study results.

But if we do take the results at face value, the VLFM data turn out to be highly inconsistent with their announced conclusion that "belief in the scientific consensus functions as an initial ‘gateway’ to changes in key beliefs about climate change, which in turn, influence support for public action.”

The authors “experimentally manipulated” the expressed estimates of the percentage of scientists who subscribe to the consensus position on climate change.

Yet the subjects whose perceptions of scientific consensus were increased in this way did not change their level of "belief" in climate change, or their support for public action to mitigate it, to an extent that differed significantly, in practical or statistical terms, from subjects who read a "placebo" story about a Star Wars cartoon series.

That information, critical to weighing the strength of the evidence in the data, was simply not reported.

VLFM have since conducted an N = 6000 "replication."  As I point out in the paper, "increasing sample" to "generate more statistically significant results" is recognized to be a bad research practice born of a bad convention--namely, null-hypothesis testing; when researchers resort to massive samples to invest minute effect sizes with statistical significance, "P values are not and should not be used to define moderators and mediators of treatment" (Kraemer, Wilson, & Fairburn 2002, p, 881). Bayes Factors or comparable statisics that measure the inferential weight of the data in relation to competing study hypotheses should be used instead (Kim & Je 2015; Raftery 1995). Reviewers will hopefully appreciate that.

But needless to say, doing another study to try to address lack of statistical power doesn't justify claiming to have found significant results in data in which they don't exist. VLFM claim that their data show that being exposed to a consensus message generated a “a significant increase” in “key beliefs about climate change” and in "support for public action" when “experimental consensus-message interventions were collapsed into a single ‘treatment’ category and subsequently compared to [a] ‘control’ group” (VLFM p. 4).  The data -- which anyone can now inspect-- say otherwise.

Hopefully reviewers will pay more attention too to  how a misspecified SEM model can conceal the absence of an experimental effect in a study design like the one reflected here (and in other "gateway belief" papers, it turns out...).

As any textbook will tell you, “it is the random assignment of the independent variable that validates the causal inferences such that X causes Y, not the simple drawing of an arrow going from X towards Y in the path diagram” (Wu & Zumbo 2007, p. 373).  In order to infer that an experimental treatment affects an outcome variable, “there must be an overall treatment effect on the outcome variable”; likewise. in order to infer that an experimental treatment affects an outcome variable through its effect on a “mediator” variable, “there must be a treatment effect on the mediator” (Muller, Judd & Yzerbyt 2005, p. 853). Typically, such effects are modeled with predictors that reflect the “main effect of treatment, main effect of M [the mediator], [and] the interactive effect of M and treatment” on the outcome variable (Kraemer, Wilson, & Fairburn 2002, p, 878).

Because the VLFM structural equation model lacks such variables, there is nothing in it that measures the impact of being “treated” with a consensus message on any of the study’s key climate change belief and attitude measures. The model is thus misspecified, pure and simple.

To illustrate this point and underscore the reporting defects in this aspect of VLFMI'll post "tomorrow" the results of a fun statistical simulation that helps to show how the misspecified VLFM model-- despite its fusillade of triple-asterisk-tipped arrows--is simply not capable of distinguishing the results a failed experiment from one that actually does support something like the “gateway model” they proposed.

BTW, I initiatlly brought all of these points to the attention of the PLOS One editorial office.  On their advice, I  posted a linke to my analyses in the comment section, after first soliciting a response from VLFM.

A lot of people are critical of PLOS ONE

I think they are being unduly critical, frankly.

The mission of the journal--to create an outlet for all valid work-- is a valuable and admirable one.

Does PLOS ONE publish bad studies? Sure. But all journals do! If they want to make a convincing case, the PLOS ONE critics should present some genuine evidence on the relative incidence of invalid studies in PLOS ONE and other journals.  I at least have no idea what such evidence would show.

But in any case, everyone knows that bad studies get published all the time-- including in the "premier" journals.

What happens next-- after a study that isn't good is published --actually matters a lot more.

In this regard, PLOS ONE is doing more than most social science journals, premier ones included, to assure the quality of the stock of knowledge that reserchers draw on.

The journal's "open data" policy and its online fora for scholarly criticsm and discussion supply scholars with extremely valuable resources for figuring out that a bad study is bad and for helping other scholars see that too.

If what's "bad" about a study is that the inferences its data support are just much weaker than the author or authors claim, other scholars will know to give the article less weight.

If the study suffers from some a serious flaw (like unreported material data or demonstrably incorrect forms of analysis), then the study is much more likely to get corrected or retracted than it would be if it managed to worm its way into a "premier" journal that lacked an open-data policy and a forum for online comments and criticism.

Peer review doesn't end when a paper is published.  If anything, that's when it starts. PLOS ONE gets that.

I do have the impression that in the social sciences, at least, a lot of authors think they can dump low quality studies on PLOS ONE.  But that's a reason to be mad at them, not the journal, which if treated appropriately by scholars can for sure help enlarge what we know about how the world works.

So don't complain about PLOS ONE. Use the procedures it has set up for post-publication peer review to make authors think twice before denigrating the journal's mission by polluting its pages with bull shit studies.

Kraemer, H.C., Wilson, G.T., Fairburn, C.G. & Agras, W.S. Mediators and moderators of treatment ef-fects in randomized clinical trials. Archives of general psychiatry 59, 877-883 (2002).

Wu, A.D. & Zumbo, B.D. Understanding and Using Mediators and Moderators. Social Indicators Re-search 87, 367-392 (2007).

Job opening for social-science editor at Nature!Dan KahanTue, 17 May 2016 13:58:47 +0000 you a trained social scientist now driving a cab (or uber-registered vehicle)?

Or a gainfully employed US social scientist looking for an exit strategy in case Donald Trump is elected president?

Well, here you go! A job at Nature!

The job itself would be lots of fun, I'm sure, but think of all the cool things you could learn from office scuttlebutt as the journal issues get put together every week!

WSMD? JA! "Confidence intervals" for "Political Polarization Literacy" testDan KahanWed, 11 May 2016 20:27:58 +0000 entry. Verified by "Virgin Mary on your French toast, you say?"™ miracle certifiersFormer Freud expert & current stats legend  Andrew Gelman and Josh " 'Hot Hand Fallay' Fallacy" Miller have announced publicly that they scored perfect 14.75's (higher, actually) on the CCP/APPC "Political Polarization Literacy" test.

They have now demanded that they be awared the "Gelman Cup." That request actually made their "political polarization literacy" scores a bit more credibile, since obviously they are too busy measuring public opinion to stay current with CCP contests and their respective prizes (I've sent them an authentic "Worrship the Industrial Strength Risk Perception Measure!" Virgin Mary Frenchtoast slice" for their performances).

But speaking of CCP games ... you guessed it: Time for another installment of

Statistical Modeling, Causal Inference, and Social Science commentator@Rahul wondered what it would look like if the plots in the "Political Polarization Literacy" test figure had confidence intervals.

Here's the answer:

(If you forgot what the policy items are, you can either go back to the original post or just click here.)

Actually, I'm not sure CIs add interesting information here.

Once one knows that the N = 1200 & the sample is representative, it's pretty easy to know what the CIs will look like (around 0.04 at pr = 0.50; smaller as one approaches pr = 0 & pr = 1.0).

The intersting information here is in the covariances of positions and left_right. The CIs don't make that any clearer; if anything, they make that a bit harder to see!  So I'd say for the purposes of the game, the lowess plots, sans CIs, were all the "statistics" & "modeling" needed for us to start learning something (about WEKS) from the data.

But that's my view. Others might disagree.

Who knows-- they might even disagree with me that "spike plots" rather than, say, colored confidence bands are a prettier way to denote 0.95 CI zones if one thinks there is something to be gained by fitting a model to data like these!

In awe of the Industrial Strength Risk Perception Measure. . . .Dan KahanTue, 10 May 2016 15:07:16 +0000 is a little postscript on yesterday’s post on the CCP/APPC "Political Polarization Literacy" test.

A smart friend asked me whether responses to the items in the “policy preferences” battery from yesterday might be different if the adjective “government” were not modifying “policies” in the introduction to the battery.

I think, frankly, that 99% of the people doing public opinion research would find this question to be a real snoozer but in fact it it’s one that ought to keep them up all night (assuming they are the sort who don’t stay up all night as a matter of course; if they are, then up all day) w/ anxiety.

It goes to the issue of what items like these are really measuring—and how one could know what they are measuring.  If one doesn’t have a well-founded understanding of what responses to survey items are measuring—if anything—then the whole exercise is a recipe for mass confusion or even calculated misdirection. I’m not a history buff but I’m pretty sure the dark ages were ushered in by inattention to the basic dimension of survey item validity; or maybe we still are in the dark ages in public opinion research as a result of this (Bishop 2005)?

In effect, my colleague/friend/collaborator/fellow-perplexed-conversant was wondering if there was something about the word “government” that was coloring responses to all the items, or maybe a good many of them, in way that could confound the inferences we could draw from particular ones of them . . . .

I could think of a number of fairly reasonable interpretive sorts of arguments to try to address this question, all of which, it seems to me, suggest that that’s not likely so.

But the best thing to do is to try to find some other way of measuring what I think the policy items are measuring, one that doesn’t contain the word “government,” and see if there is agreement between responses to the two sets of items. If so, that supplies more reason to think, yeah, the policy items are measuring what I thought; either that or there is just a really weird correspondence between the responses to the items—and that’s less a likely possibility in my view.

What do I think the “policy” items are measuring?  I think the policy items are measuring, in a noisy fashion (any single item is noisy)  pro- or con- latent or unobserved attitudes toward particular issues that themselves are expressions of another latent attitude, measured (nosily but less so  because there are two “indicators” or indirect measures of it) by the aggregation of the “partisan self-identification” and “liberal-conservative” ideology items that “Left_right” comprise.

That’s what I think risk perception measures are too—observable indicators of a latent pro- or con-affective attitude, one that often is itself associated with some more remote measure of identity of the sort that could be measured variously with either cultural worldview items, religiosity, partisan political identity, and the like (see generally Peters & Slovic 1996; Peters Burraston & Mertz 2004; Kahan 2009).

The best single indicator I can think of for latent affective attitudes is . . . the Industrial Strength Risk Perception Measure!

As the 14 billion readers of this blog know, ISRPMs consist in 0-7 or 0-10 rankings of the “risk” posed by a putative risk source. I’m convinced it works best when each increment in the Likert scale has a descriptive label, which favors 0-7 (hard to come up w/ 10 meaningful labels).

As I’ve written about before, the ISRPM has a nice track record.  Basically, so long as the putative risks source is something people have a genuine attitude about (e.g., climate change, but not GM foods), it will correlate pretty strongly with pretty much anything more specific you ask (is climate change happening? are humans causing it? are wesa gonna die?) relating to that risk.  So that makes the ISRPM a really economical way to collect data, which can then be appropriately probed for sources of variance that can help explain who believes what & why about the putative risk source.

It also makes it a nice potential validator of particular items that one might think are measuring the same latent attitude.  If those items are measuring what you think, they ought to display the same covariance patterns  that corresponding ISRPMs do in relation to whatever latent identity one posits explains variance in the relevant ISRPM.

With me? Good!

Now the nice thing here is that the ISRPM measure, as I use it, doesn’t explicitly refer to “government." The intro goes like this ...

and then you have individual "risk sources," which, when I do a study at least, I always randomize the order of & put on separate "screens" or "pages" so as to minimize comparative effects:

Obviously, certain items on an ISRPM  battery will nevertheless imply government regulation of some sort.

But that’s true for the “policy item” batteries, the validity of which was being interrogated (appropriately!) by my curious friend.

So, my thinking went, if the ISRPM items had the same covariance pattern as the policy items in respect to “Left_right,” the latent identity attitude formed by aggregation of a 7-point political identity item and a 5-point liberal conservative measure, that would be a pretty good reason to think (a) the two are measuring the same “latent” attitude and (b) what they are measuring is not an artifact of the word “government” in the policy items—even if attitudes about government might be lurking in the background (I don’t think that in itself poses a validity problem; attitudes toward government might be integral to the sorts of relationships between identity and “risk perceptions” and related “policy attitudes” variance in which we are trying to explain).

So. . .

I found 5 “pairs” of policy-preference items an corresponding ISRPMs.

The policy-preferences weren’t all on yesterday’s list. But that’s because only some of those had paired ISRPMs.  Moreover, some ISRPMs had had corresponding policy items not on yesterday’s list.  But I just picked the paired ones on the theory that covariances among “paired items” would give us information about the performance of items on the policy list generally, and in particular whether the word “government” matters.

Here are the corresponding pairs:

I converted the responses to z-scores, so that they would be on the same scale. I also reverse coded certain of the risk items, so that they would have the same valence (more risk -> support policy regulation; less risk -> oppose).

Here are the corresponding covariances of the responses to the items—policy & ISRPM—in relation to Left_right, the political outlook scale

Spooky huh?!  It’s harder to imagine a tighter fit!

Note that the items were administered to two separate samples

That’s important! Otherwise, I’d attribute this level of agreement to a survey artifact: basically, I’d assume that respondents were conforming their answer to whichever item (ISRPM or policy) that came second so that it more or less cohere with the one they gave to the first.

But that’s not so; these are response from two separate groups of subjects, so the parallel covariances gives us really good reason to believe that the “policy” items are measuring the same thing as the ISRPMs—and that the world “government” as it appears in the former isn’t of particular consequence.

If, appropriately, you want to see the underlying correlation matrix in table form, click here (remember, the paired items were administered to two separate samples so we have no information about their correlation with each other--only their respective correlations with left_right.)

So two concluding thoughts:

1. The question "what the hell is this measuring??," and being able to answer it confidently, are vital to the project of doing good opinion research.  It is just ridiculous to assume that survey items think they are measuring what you think; you have to validate them.  Otherwise, the whole enterprise becomes a font of comic misunderstanding.

2. We should all be friggin’ worshiping ISRPM!

I keep saying that it has this wonderful quality, as a single-item measure, to get at latent pro-/con- attitudes toward risk; that responses to it are highly likely to correlate with more concrete questions we can ask about risk perceptions, and even with behavior in many cases.  There’s additional good research to support this.

But to get such a vivid confirmation of its miraculous powers in a particular case! Praise God!

It’s like seeing Virgin Mary on one’s French Toast!

Kahan, D.M. Nanotechnology and society: The evolution of risk perceptions. Nat Nano 4, 705-706 (2009).

Peters, E. & Slovic, P. The Role of Affect and Worldviews as Orienting Dispositions in the Perception and Acceptance of Nuclear Power. J Appl Soc Psychol 26, 1427-1453 (1996).

Hey everybody -- take the cool CCP/APPC "Political Polarization Literacy" test!Dan KahanMon, 09 May 2016 02:37:35 +0000 we, unlike certain other sites that I won’t deign to identify, actually listen to our 14 billion regular readers, CCP Blog is adding yet another member to its stable of wildly popular games (which, of course, include MAPKIA!, WSMD? JA!, & HFC! CYPHIMU?): the CCP/APPC “Political Polarization Literacy” Test!

Official game motto: “Because the one thing we all ought to agree on is what we disagree about!”

Ready . . . set . . . open your test booklet and begin!

Match the policies on this list . . .

to the plotted lines in this figure:

Take your time, no rush.

Keep going.

Scroll down when the proctor declares that the exam is over.

If you finish early, feel free to click on the random ass pictures that I've inserted to prevent you from inadverently spotting the answers before completing the test!

On their way to Canada, possibly?

Time’s up!

Okay, here’s what I’m going to do.  First, I’m going to start by showing you the “answer key,” which consists of the original figure with labels.

Second, I’m going to tell you how to score your answers.

To do that, I’ll display separate figures for (a) policies that are strongly polarizing; (b) policies that are weakly polarizing; (c) policies that reflect bipartisan ambivalence; and (d) policies that reflect bipartisan support. In connection with each of these figures, I’ll supply scoring instructions.

So . . .

“Answer key”

Point-score figures

1. Strongly polarizing

Award yourself (or your child or pet, if you are scoring his or her test) 1 point for each policy that appears in this set and that you (or said child or pet) matched with any of these five plotted lines regardless of which of the lines you actually matched it with.

Got that? No? Okay, well, e.g., if you matched “stricter carbon emission standards to reduce global warming” with the “magenta” colored line you get 1 point; but you also get 1 point if you matched it with red, blue, midblue, or cyan-colored lines. Same for every other friggin’ policy in this set—okay?

Good. Now give yourself (et al.) a 3-point bonus if you matched “Gay marriage (allowing couples of the same sex to marry each other)” with any of the plotted lines depicted in this figure.

2. Weakly polarizing

Award yourself (et al.) 1.5 points for each policy in this set that you (enough of this) matched with either of the two plotted lines in this figure.

3. Bipartisan ambivalence

Award yourself 0.75 points if you got this one.

4. Bipartisan support

Award yourself 3 points if you matched “Approval of an amendment to the U.S. constitution that would allow Congress and state legislatures to prohibit corporations from contributing money to candidates for elected office” with either of the plotted lines in this figure.

Subtract 5 points if you failed to match “Requiring children who are not exempt for medical reasons to be vaccinated against measles, mumps, and rubella” with one of the two lines in this figure.

Subtract 5 points if you matched “Gay marriage (allowing couples of the same sex to marry each other)” with either of the two lines in this figure.

17: you are a cheater and are banned from this site until Pete Rose is inducted into the Baseball Hall of Fame, Hell Freezes Over, or Donald Trump is elected President, whichever happens first.

14.75: you are either a “political polarization genius,” pr = 0.25, or a liar, pr = 0.75.

10-14.74: Damn! You are one of the 14 billion regular readers of this blog!

5-10: Meh.

0-4: Not awful.

-10: You win! Obviously you have better things to do with your time than waste them viewing the sad spectacle of unreason that our democracy has become!  (But what the hell are you doing on this site?)

Now, some explanation on the scoring.

It was done by a Hal9001 series super computer,  which designed the “game” (obviously if you missed anything, that is due to human error).

But note that the Hal9001 put a lot emphasis on two policies in particular:

The reason, I’m told by Hal9001, is that getting these ones wrong is a sign that your child or pet (obviously, we aren’t talking about you here!) is over-relying on heuristic, Political Polarization System 1 reasoning.  As a result, your child or pet is succumbing to the extremely common “what everyone knows syndrome,” or WEKS, a bias that consists in, well, treating “what everyone knows” as evidence.

Or more specifically, treating as evidence the views of the biased sample (in a measurement sense, not necessarily a cognitive or moral one) of people who one happens to be exposed to disproportionately as a result of the natural, understandable tendency to self-select into “discourse communities” populated w/ people who basically have relatively uniform outlooks and motivations and experiences.

For sure WEKS biases people’s opinions on public opinion vaccines.

There is overwhelming empirical evidence of public support for universal immunization across all political, cultural, religious, etc. groups. Yet commentators, treating each other’s views as evidence,  keep insisting that either one group or another (“the conservative don’t-tread-on-me crowd that distrusts all government recommendations,” “limousine liberals,” blah blah) is hostile to vaccines or even  more patently false a “growing distrust of vaccinations” among  “a large and growing number” of “otherwise mainstream parents.”  And lots of people assume, gee, if “everyone knows that” it must be true!

Same on gay marriage.

In the sources that people on the “left” consult, “everyone knows that” there has been an been “an astounding transformation of public opinion.”  They constantly call for "replicating the success of marriage equality" on climate change, e.g.

Actually, the “transformation” on gay marriage was primarily just a bulging of public support among people on the “left.” Support among people who identify as “liberal” grew from 56% to 79%, and among those who identify as Democrat from 43% to 66%, in the period from 2000 to 2015; among self-identified “conservatives” and Republicans, the uptick was much more modest--from 18% to 30% and 21% to 32% respectively.

That’s a shift, sure. But 79%:30%/66%:32% is . . . political polarization.

The “how to replicate gay marriage” on climate change meme rests on a faulty WEKS premise or set of them.

One is that Gay marriage isn’t as divisive than climate change. It is.  Or if it isn't, it's only because  there is still a higher probability that a “liberal Democrat” and a “conservative Republican” will agree that gay marriage shouldn’t be legalized than they will agree that the U.S. should or shouldn’t adopt “stricter carbon emission standards to reduce global warming.”

Maybe climate change advocates should "replicate the success" of gun control advocates and affirmative action proponents, too?

Another faulty premise has to do with the instrument of legal change in gay marraiage.

Legalization of gay marriage occurred primarily by judicial action, not legislation: of the 37 states where gay marriage was already legally recognized before the U.S. Supreme Court decided Obergefell v. Hodges, 26 were in that category as a result of judicial decisions invalidating apparently popularly supported legal provisions (like California’s 2008 popular referendum “Prop. 8”) disallowing it.

Those judicial decisions, in my view, were 100% correct: the right to pursue one’s own conception of happiness in this way shouldn’t depend on popular concurrence.

But I don't think it's a good idea to propogate a false narrative about what really happened here or about what today’s reality is.   False narratives, underwritten by WEKS, lead people to make mistakes in their practical decisionmaking.

Indeed, WEKS-- the disposition of people to confuse the views of people who share one's outlooks, motivations, experience as “evidence” of how the world works—on public opinion and other topics too is one of the reasons we have polarization on facts that admit of being assessed with valid empirical evidence.

One of the reasons in other words that we are playing this stupid game.

Raw data: the best safeguard against empirical bull shit!Dan KahanFri, 06 May 2016 04:52:27 +0000 last two posts were so shockingly well received that it seemed appropriate to follow them up w/ one that combined their best features: (a) a super smart guest blogger; (b) a bruising, smash-mouthed attack against those who are driving civility from our political discourse by casting their partisan adversaries as morons; and (c) some kick-ass graphics that are for sure even better than "meh" on the Gelman scale!

The post helps drive home one of the foundational principles of critical engagement with empirics: if you don't want to be the victim of bull-shit, don't believe any statistical model before you've been shown the raw data!

Oh-- and I have to admit: This is actually a re-post from So if 5 or 6 billion of you want to terminate your subscription to this blog & switch over to that one after seeing this, well I won''t blame you --  now I really think Gelman was being kind when he described my Figure as merely "not wonderful...."

When studies studying bullshit are themselves bullshit...

We have a problem wth PLoS publishing bullshit studies.

Look, I really appreciate some aspects of PLoS. I like that they require people to share data. I like that they will publish null results. However, I really hope that someday the people who peer-review papers for them step up their game.

This evening, I read a paper that purports to show a relationship between seeing bullshit statements as profound and support for Ted Cruz.

The paper begins with an interesting premise: does people's bullshit receptivity--that is, their perception that vacuous statements contain profundity--predict their support for various political candidates? This is a particularly interesting question. I think we can all agree that politicians are basically bullshit artists

Specifically, though, the authors are not examining people's abilities to recognize when they are being lied to; they define bullshit statements as

communicative expressions that appear to be sound and have deep meaning on first reading, but actually lack plausibility and truth from the perspective of natural science.

OK, they haven't lost me yet.

The authors then reference some recent literature that has describes conservative ideology as what amounts to cognitive bias (at the least) and mental defect (at the worst).

I identify as liberal. However, I think that this is the worst kind of motivated reasoning on the part of liberal psychologists.  Some of this work has been challenged (see Kahan take on some of these issues). But let's ignore this for right now and pretend, that the research they are citing here is not flawed.

The authors have the following hypotheses:

  • Conservativism will predict judging bullshit statements as profound. (I can tell you right off that if this were mostly a conservative issue, websites like spirit science would not exist)
  • The more individuals have favorable views of Republican candidates, the more they will see profoundness in bullshit statements. (So here, basically using support for various candidates as another measure of conservativism).
  • Conservativism should not be significantly related to seeing profoundness in mundane statements.
These hypotheses were clearly laid out, which I appreciate. I also appreciate that the authors followed the guidelines and posted their data. Makes post-publication peer-review possible.

Here is one of my first criticisms of the method of this paper. The authors chose to collect a sample of 196 participants off of Amazon's Mechanical Turk. Now, I understand why, MTurk is a really reasonably priced way of getting participants who are not psych 101 undergraduates. However, there are biases with MTurk samples. Mainly that they are disproportionately male, liberal, and educated. Particularly when researchers are interested in examining questions related to ideology, MTurk is not your best bet. But, let's take a look at the breakdown of their sample based on ideology, just to check--especially since we know that they want to make inferences about conservatives in particular.
I don't have the exact wording of their measure of conservativism, but they describe it as asking participants to place themselves on a 7-point Likert scale where 1 is liberal and 7 is conservative. The above table shows the frequency of participants at each level. You can see that the sample is disproportionately liberal/liberal leaning. In fact, if you total the participants in columns 5, 6, and 7 (the more conservative columns), you have a whopping total of 46 participants choosing a somewhat conservative designation versus the 108 participants in columns 1, 2, and 3.

Thus, it is unfair--in my opinion--to think that you can really make inferences about conservatives in general from this data. Many studies in political science and communications use nationally-representative data with over 1500 participants. At Annenberg Public Policy Center we get uncomfortable sometimes making inferences from our pre/post panel data (participants who we contact two times) because we end up with only around 600. I'm not saying that it is impossible to make inferences from less than 200 participants, but that the authors should be very hesitant, particularly when they have a very skewed sample.

I'm going to skip past analyzing the items that they use for their bullshit and mundane statements. It would be worth doing a more comprehensive item analysis on the bullshit receptivity scale--at least going beyond reporting Cronbach's alpha. But, that can be done another time.

The favorability ratings of the candidates are another demonstration of how the sample is skewed. The sample demonstrates the highest support for Bernie Sanders and the lowest support for Trump.
This figure shows the density of participants rating four of the candidates (the authors also include Martin O'Malley and Marco Rubio) on the 5 point scale. You can see that a huge proportion of participants gave Trump and Cruz the lowest rating. In contrast, People tended to like Clinton and Sanders more.

Moving onto their results.

The main claim that the authors make is that:
Favorable ratings of Ted Cruz, Marco Rubio, and Donald Trump were positively related to judging bullshit statements as profound, with the strongest correlation for Ted Cruz. No significant relations were observed for the three democratic candidates.
Now, the authors recognized that their samples were skewed, so they conducted non-parametric correlations. But, I'm not sure why the authors didn't simply graph the raw data and look at it.

Below, I graph the raw data with the bullshit receptivity scores on the x-axis and the support scores for each candidate on the y-axis. The colored line is the locally-weighted regression line and the black dashed line treats the model as linear. I put Ted Cruz first, since he's the one that the authors report the "strongest" finding for.
So, does this look like a linear relationship to you? As the linear model goes up (which I imagine is what drives the significant correlation), the loess line goes down. I imagine that this is a result fo the outliers who score high on BSR. Note that of the ones scoring highest on BSR, the largest clump actually shows low support for Cruz, with one outlier rating him at 4. Indeed, the majority of the sample sits at 1 for supporting Ted cruz, and the samples' BSR scores are grouped in the middle.

You can see similar weirdness for the Trump and Rubio Ratings. The Trump line is almost completely flat--and if we were ever to think that support for a candidate predicted bullshit receptivity, it would be support for Trump---but I digress.... Note, too, how low support is.  Rubio, on the other hand, shows a light trend upwards when looking at the linear model (the black dashed line), but most people are really just hovering around the middle. Like with Cruz, the people with the highest bullshit receptivity (scores of around 5) rate Rubio low (1 or 2).

So, even if I don't agree that your significant correlations are meaningful for saying that support for conservatives is predicted by bullshit receptivity (or vice versa), you might still argue that there is a difference between support for liberals and support for conservatives. So, let's look at the democratic candidates.
I put Hillary Clinton on top, because I want to point out that her graph doesn't look much different from that of Cruz or Rubio. It still has a trend upwards, but not just for the linear model. In fact, where Cruz had one person that gave high ratings for him and had the highest level of bullshit receptivity, Hillary has three.  In fact, let's take a look at Clinton's loess Line and Cruz's loess line mapped on the same figure....
Kind of looks to me like there is a stronger argument for Clinton supporters having more bullshit receptivity. Now, I do support Hillary Clinton, so don't get me wrong. My point is only to demonstrate that significant p values for one type of correlation do not mean that the finding is real.

Here are the figures for Sanders and O'Malley. Again, pretty straight lines. But for the highest level of bullshit receptivity, Bernie indeed has a cluster of supporters--people rating him at the highest level. I do not think that this supports the opposite conclusion to what these authors found--that bullshit receptivity predicts democratic candidate support--but I don't think that the authors should have made the conclusions that they did. These results really just appear to be noise to me.
In conclusion...

The authors *do* list the limitations of their study. They state that their research is correlational and that their sample was not nationally representative. But they still make the claim that conservatism is related to seeing profoundness in bullshit statements.. Oh, which reminds me, we should have looked at that too...
That's a graphical representation of conservatism predicting bullshit receptivity.

What concerns me, here, is two-fold.

First, despite what p values may or may not be below a .05 threshold, there is no reason to think that this data actually demonstrates that conservatives are more likely to see profundity in bullshit statements than liberals--But the media will love it.

Moreover, there is no reason to believe that such bullshit receptivity predicts support for conservative candidates--but the media will love it. This is exactly the type of fodder picked up  because it suggests that conservatism is a mental defect of some sort. It is exciting for liberals to be able to dismiss conservative worldviews as mental illness or as some sort of mental defect. However, rarely do I think these studies actually show what they purport to. Much like this one.

Second, it is this type of research that makes conservatives skeptical of social science. Given that these studies set out to prove hypotheses that conservatives are mentally defective, it is not surprising that conservatives become skeptical of social science or dismiss academia as a bunch of leftists. Check out this article on The Week about the problem of liberal bias in social science

If we actually have really solid evidence that conservatives are wrong on something, that is totally great and fine to publish. For instance, we can demonstrate a really clear liberal versus conservative bias in belief of climate change. But we have to stop trying to force data to fit the view that conservatives are bad. I'm not saying that this study should be retracted,  but it is indicative of a much larger problem with the trustworthiness of our research.
Bounded rationality, unbounded out-group hateDan KahanSat, 30 Apr 2016 04:04:23 +0000  By popular demand & for a change of pace ... a guest post from someone who actually knows what the hell he or she is talking about!

Bias, Dislike, and Bias

Daniel Stone

Read this! Or you are just a jerk, like all the other members of your stupid political party!Thanks Dan K for giving me the chance to post here.  Apologies - or warning at least - the content, tone etc might be different from what's typical of this blog.  Rather than fake a Kahan-style piece,[1] I thought it best to just do my thing.  Though there might be some DK similarity or maybe even influence.  (I too appreciate the exclamation pt!)

Like Dan, and likely most/all readers of this blog, I am puzzled by persistent disagreement on facts.  It also puzzles me that this disagreement often leads to hard feelings.  We get mad at - and often end up disliking - each other when we disagree.  Actually this is likely a big part of the explanation for persistent disagreement; we can't talk about things like climate change and learn from each other as much as we could/should - we know this causes trouble so we just avoid the topics. We don’t talk about politics at dinner etc.  Or when we do talk we get mad quickly and don’t listen/learn.  So understanding this type of anger is crucial for understanding communication.

It's well known, and academically verified, that this is indeed what's happened in party politics in the US in recent decades - opposing partisans actually dislike each other more than ever.  The standard jargon for this now is 'affective polarization'.  Actually looks like this is the type of polarization where the real action is since it’s much less clear to what extent we’ve polarized re policy/ideology preferences- though it is clear that politician behavior has diverged - R's and D's in Congress vote along opposing party lines more and more over time.  For anyone who doubts this, take a look at the powerful graphic in inset to the left, stolen from this recent article.

So—why do we hate each other so much?

Full disclosure, I'm an outsider to this topic.  I'm an economist by training, affiliation, methods.  Any clarification/feedback on what I say here is very

The fingerprint(s) of polarization in Congress....

Anyway my take from the outside is the poli-sci papers on this topic focus on two things, "social distance" and new media.  Social distance is the social-psych idea that we innately dislike those we feel more "distance" from (which can be literal or figurative).  Group loyalty, tribalism etc.  Maybe distance between partisans has grown as partisan identities have strengthened and/or because of gridlock in DC and/or real/perceived growth in the ideological gap between parties.  New media includes all sorts of things, social media, blogs, cable news, political advertising, etc.  The idea here is we're exposed to much more anti-out party info than before and natural this would sink in to some extent.

There's a related but distinct and certainly important line of work in moral psychology on this topic – if you’re reading this there’s a very good chance you’re familiar with Jonathan Haidt's book The Righteous Mind in particular.  He doesn't use the term social distance but talks about a similar (equivalent?) concept—differences between members of the parties in political-moral values and the evolutionary explanation for why these differences lead to inter-group hostility.

So—this is a well-studied topic that we know a lot about.  Still, we have a ways to go toward actually solving the problem.  So there’s probably more to be said about it.

Here’s my angle: the social distance/Haidtian and even media effects literatures seem to take it as self-evident that distance causes dislike.  And the mechanism for this causal relationship is often treated as black box.  And so, while it’s often assumed that this dislike is “wrong” and this assumption seems quite reasonable—common sense, age-old wisdom etc tell us that massive groups of people can’t all be so bad and so something is seriously off when massive groups of people hate each other—this assumption of wrongness is both theoretically unclear and empirically far from proven.

Citizens of the the Liberal Republic of Science-- unite against partyism!But in reality when we dislike others, even if just because they’re different, we usually think (perhaps unconsciously) they’re actually “bad” in specific ways.  In politics, D’s and R’s who dislike each other do so (perhaps ironically) because they think the other side is too partisan—i.e. too willing to put their own interests over the nation’s as a whole.  Politicians are always accusing each other of “playing politics” over doing what’s right.  (I don’t know of data showing this but if anyone knows good reference(s) please please let me know.)

That is, dislike is not just “affective” (feeling) but is “cognitive” (thinking) in this sense.  And cognitive processes can of course be biased.  So my claim is that this is at least part of the sense in which out-party hate is wrong—it’s objectively biased.  We think the people in the other party are worse guys than they really are (by our own standards).  In particular, more self-serving, less socially minded.

This seems like a non-far-fetched claim to me, maybe even pretty obviously true when you hear it.  If not, that’s ok too, that makes the claim more interesting.  Either way, this is not something these literatures (political science, psychology, communications) seem to talk about.  There is certainly a big literature on cognitive bias and political behavior, but on things like extremism, not dislike.

Here come the semi-shameless[2] plugs.  This post has already gotten longer than most I’m willing to read myself so I’ll make this quick.

In one recent paper, I show that ‘unrelated’ cognitive bias can lead to (unbounded!) cognitive (Bayesian!) dislike even without any type of skewed media or asymmetric information.

In another, I show that people who overestimate what they know in general (on things like the population of California)--and thus are more likely to be overconfident in their knowledge in general, both due to, and driving, various more specific cognitive biases--also tend to dislike the out-party more (vs in-party), controlling carefully for one’s own ideology, partisanship and a bunch of other things.

Feedback on either paper is certainly welcome, they are both far from published.

So—I’ve noted that cognitive bias very plausibly causes dislike, and I’ve tried to provide some formal theory and data to back this claim up and clarify the folk wisdom that if we understood each other better, we wouldn’t hate each other so much.  And dislike causes (exacerbates) bias (in knowledge, about things like climate change, getting back to the main subject of this blog).  Why else does thinking of dislike in terms of bias matter?  Two points.

1) This likely can help us to understand polarization in its various forms better.  The cognitive bias literature is large and powerful, including a growing literature on interventions (nudges etc).  Applying this literature could yield a lot of progress.

2) Thinking of out-party dislike (a.k.a. partyism) as biased could help to stigmatize and as a result reduce this type of behavior (as has been the case for other 'isms').  If people get the message that saying “I hate Republicans” is unsophisticated (or worse) and thus uncool, they’re going to be less likely to say it.

For a decentralized phenomenon like affective polarization, changing social norms may ultimately be our best hope.

[1] Ed.: Okay, time to come clean. What he's alluding to is that I've been using M Turk workers to ghost write my blog posts for last 6 mos. No one having caught on, I’ve now decided that it is okay after all to use M Turk workers in studies of politically motivated reasoning.

[2] Ed.: Yup, for sure he is not trying to imitate me. What’s this “semi-” crap?


Harry Potter

Why I’m excited (and nervous) about Ginny’s presence in ‘Harry Potter and the Cursed Child’

‘Harry Potter and the Cursed Child’ reveals first looks at Harry, Ginny and Albus Potter

Harry Potter and the Cursed Child begins previews in London next week, and now photos of the main cast are beginning to surface.

Don’t panic ‘Harry Potter’ fans, but J.K. Rowling says ‘Cursed Child’ will make you cry

Harry Potter and the Cursed Child is set to continue Harry, Ron and Hermione’s story. Downside: The characters that survived Deathly Hallows are suddenly no longer safe!

Latest viral ‘Harry Potter’ fan theory tragically reveals why Harry’s Hogwarts class was abnormally small

A Harry Potter fan has had a sudden and sad realization about why the Chosen One’s Hogwarts class was smaller than usual.

Fun fact: J.K. Rowling told us all about American Quidditch years ago

As we await this November’s release of the North America-set Fantastic Beasts, many are wondering if we’ll be hearing about an American Wizarding Sport like Quidditch.

England’s biggest bookstore announces first ‘Cursed Child’ midnight release party

Congratulations to Waterstones Piccadilly, who is the first bookstore in the world* to announce their Harry Potter and the Cursed Child midnight release party.

J.K. Rowling casts an Expecto Patronum spell for a fan in need (Update: Buy it, support charity)

When a Harry Potter fan needed help from J.K. Rowling on Wednesday, she received a powerful spell from the author over Twitter.

Eddie Redmayne joins voice cast for ‘prehistoric soccer’ animation ‘Early Man’

Fantastic Beasts superstar Eddie Redmayne is lending his voice to an animated movie about prehistoric soccer players. What’s not to love?!

Ilvermorny’s 4 houses unveiled thanks to secret code found on Pottermore

The names of the four houses that make up Harry Potter author J.K. Rowling’s North American Wizarding School, Ilvermorny, appear to have surfaced online.


Most Cited Behavioural Processes Articles

The most cited articles published since 2011, extracted from Scopus.

Delay discounting: Trait variable?
Amy L. Odum
Delay discounting refers to the tendency for outcomes that are remote in time to have less value than more immediate outcomes. Steep discounting of delayed outcomes is associated with a variety of social maladies. The degree of sensitivity to delayed outcomes may be a stable and pervasive individual characteristic. In analyses of archival data, the present study found positive correlations between the degree of delay discounting for one outcome (as measured by the Area Under the Curve), and the degree of discounting for other outcomes. Along with additional evidence reviewed, these data suggest that delay discounting may be considered a personality trait. Recent research in epigenetics, neuroscience, and behavior suggests delay discounting may prove to be a beneficial target for therapeutic attempts to produce global reductions in impulsivity related to delay discounting. © 2011 Elsevier B.V.

Border collie comprehends object names as verbal referents
John W. Pilley | Alliston K. Reid

Koji Jimura | Joel Myerson | Joseph Hilgard | Julia Keighley | Todd S. Braver | Leonard Green
Individual discounting rates for different types of delayed reward are typically assumed to reflect a single, underlying trait of impulsivity. Recently, we showed that discounting rates are orders of magnitude steeper for directly consumable liquid rewards than for monetary rewards (Jimura et al., 2009), raising the question of whether discounting rates for different types of reward covary at the individual level. Accordingly, the present study examined the relation between discounting of hypothetical money and real liquid rewards in young adults (Experiment 1) and older adults (Experiment 2). At the group level, young adults discounted monetary rewards more steeply than the older adults, but there was no significant age difference with respect to liquid rewards. At the individual level, the rates at which young and older participants discounted each reward type were stable over a two- to fifteen-week interval (rs > 70), but there was no significant correlation between the rates at which they discounted the two reward types. These results suggest that although similar decision-making processes may underlie the discounting of different types of rewards, the rates at which individuals discount money and directly consumable rewards may reflect separate, stable traits, rather than a single trait of impulsivity. © 2011 Elsevier B.V.

Mark E. Bouton | Neil E. Winterbauer | Travis P. Todd
It is widely recognized that extinction (the procedure in which a Pavlovian conditioned stimulus or an instrumental action is repeatedly presented without its reinforcer) weakens behavior without erasing the original learning. Most of the experiments that support this claim have focused on several "relapse" effects that occur after Pavlovian extinction, which collectively suggest that the original learning is saved through extinction. However, although such effects do occur after instrumental extinction, they have not been explored there in as much detail. This article reviews recent research in our laboratory that has investigated three relapse effects that occur after the extinction of instrumental (operant) learning. In renewal, responding returns after extinction when the behavior is tested in a different context; in resurgence, responding recovers when a second response that has been reinforced during extinction of the first is itself put on extinction; and in rapid reacquisition, extinguished responding returns rapidly when the response is reinforced again. The results provide new insights into extinction and relapse, and are consistent with principles that have been developed to explain extinction and relapse as they occur after Pavlovian conditioning. Extinction of instrumental learning, like Pavlovian learning, involves new learning that is relatively dependent on the context for expression. © 2012 Elsevier B.V.

Time estimation of fear cues in human observers
Erich K. Grommet | Sylvie Droit-Volet | Sandrine Gil | Nancy S. Hemmes | A. Harvey Baker | Bruce L. Brown
Previous research suggests that time judgments are a function of the affective properties of to-be-timed stimuli and that time judgments are longer for stimuli that are fear-inducing (e.g., Hare, 1963; Watts and Sharrock, 1984). The goals of the present study were twofold: to replicate the effect of a fear cue on time estimation, and to evaluate the mechanism underlying the effect. Seven stimulus durations in two different duration ranges (short: 250-1000. ms; long: 400-1600. ms) were employed in the bisection procedure. Adult human participants were exposed to two successive sessions, one each with the short and long range. Images from the International Affective Picture System (IAPS; Lang et al., 2008) that were rated on three scales including arousal and fear were presented as temporal stimuli. Three images that were rated high on fear and three rated low served as fear cues and neutral control images, respectively. Results indicated that for both ranges, judgments were longer for fear cues than for neutral images, and that the magnitude of the effect did not differ between ranges as measured by the bisection point. Application of scalar expectancy theory (SET; Gibbon, 1977; Church, 1984) to these results suggests that the fear effects were mediated by switch latency of an internal clock, rather than by clock speed. © 2010 Elsevier B.V.

Sarah E. Overington | Laure Cauchard | Kimberly Ann Côté | Louis Lefebvre
Innovative foraging behaviour has been observed in many species, but little is known about how novel behaviour emerges or why individuals differ in their propensity to innovate. Here, we investigate these questions by presenting 36 wild-caught adult male Carib grackles (Quiscalus lugubris) with a novel problem-solving task. Twenty birds solved the task (" innovators") while 16 did not (" non-innovators"). We compared innovators to non-innovators and explored variation in latency to innovate to determine the characteristics of an innovative bird. Innovativeness was not predicted by any morphological trait, but innovators had higher exploration scores and lower object neophobia scores than non-innovators. Within the innovators, latency to innovate was positively correlated with learning speed. Video analysis also revealed a marked difference in the way individuals interacted with the novel apparatus: when innovators contacted the correct part of the apparatus, they continued to do so until they solved the problem. Non-innovators often contacted the correct part of the apparatus, but did not persist in doing so. The importance of obstacle movement cues was confirmed by an experiment where they were manipulated. © 2011 Elsevier B.V.

C. Muro | R. Escobedo | L. Spector | R. P. Coppinger
We have produced computational simulations of multi-agent systems in which wolf agents chase prey agents. We show that two simple decentralized rules controlling the movement of each wolf are enough to reproduce the main features of the wolf-pack hunting behavior: tracking the prey, carrying out the pursuit, and encircling the prey until it stops moving. The rules are (1) move towards the prey until a minimum safe distance to the prey is reached, and (2) when close enough to the prey, move away from the other wolves that are close to the safe distance to the prey. The hunting agents are autonomous, interchangeable and indistinguishable; the only information each agent needs is the position of the other agents. Our results suggest that wolf-pack hunting is an emergent collective behavior which does not necessarily rely on the presence of effective communication between the individuals participating in the hunt, and that no hierarchy is needed in the group to achieve the task properly. © 2011 Elsevier B.V.

Novel object exploration in mice: Not all objects are created equal
Charles J. Heyser | Anthony Chemero
Object exploration is an increasingly popular experimental paradigm in behavioral sciences. We have begun a series of studies with mice specifically looking at the parameters that influence behaviors in this test. The aim of the present study was to examine the effect of object type on performance in the object exploration test. More specifically, adult male C57BL/6J mice were trained and tested using objects that could be climbed (CLIMB) or with those that could only be touched (TOUCH). The results show that activity is affected by the presentation of objects, with object type interacting with some of these changes. C57 mice explored objects that can be climbed over significantly longer than objects that can only be touched and a more rapid habituation was observed using objects that could only be touched. Robust recognition memory was observed in both groups of mice, however mice in the CLIMB group exhibited a significantly greater discrimination index compared to mice in the TOUCH group. Taken together, these findings demonstrate that the selection of objects is of critical importance and it is recommended that special attention be given to the functional (affordant) properties of the objects to-be-used in future studies. © 2011 Elsevier B.V.

Locomotor behaviors in zebrafish (Danio rerio) larvae
Ruth M. Colwill | Robbert Creton
Locomotor behaviors were examined in two experiments using zebrafish (Danio rerio) larvae at 4, 5, 6 and 7 days post fertilization (dpf). Larvae were observed in individual wells of a 12-well plate for 1. h a day. In Experiment 1, the same larvae were observed for four consecutive days beginning on post-fertilization day 4; in Experiment 2, different groups of larvae from the same egg collection were observed at 4, 5, 6 and 7. dpf. Automated images collected every 6. s were analyzed for information about larval location, orientation and general activity. In both experiments, 4. dpf larvae rested significantly more, used a smaller area of the well more frequently, and were generally less active than older larvae. All larvae exhibited a preference for facing away from the center of the well and for the edge of the well. However, prolonged exposure to the well influenced overall activity, orientation, and preference for the edge region. The implications of these results for understanding the development of larval behavior and for the design of procedures to measure the effects of experience in zebrafish larvae are discussed. © 2011 Elsevier B.V.

Sensory basis of vigilance behavior in birds: Synthesis and future prospects
Esteban Fernández-Juricic
Birds gather visual information through scanning behavior to make decisions relevant for survival (e.g., detecting predators and finding food). The goal of this study was (a) to review some visual properties involved in scanning behavior (retinal specialization for visual resolution and motion detection, visual acuity, and size of the blind area), and (b) hypothesize how the inter-specific variability in these properties may lead to different scanning strategies. The avian visual system has a high degree of heterogeneity in visual performance across the visual field, with some sectors providing higher levels of visual resolution and motion detection (e.g., retinal specializations) than others (e.g., peripheral retina and blind area). Thus, information quality will vary in different parts of the visual field, which contradicts some theoretical assumptions on information gathering. Birds need to move their eyes and heads to align the retinal specializations to different sectors of visual space. The rates of eye and head movements can then be used as proxies for scanning strategies. I propose specific predictions as to how each of the visual properties studied can affect scanning strategies in the context of predator detection in different habitat types and with different levels of predation risk. Establishing the degree of association between sensory specializations and scanning strategies can enhance our understanding of the evolution of anti-predator behavior. © 2011 Elsevier B.V.

Peter R. Killeen
Behavior such as depression of a lever or perception of a stimulus may be strengthened by consequent behaviorally significant events (BSEs), such as reinforcers. This is the Law of Effect. As time passes since its emission, the ability for the behavior to be reinforced decreases. This is trace decay. It is upon decayed traces that subsequent BSEs operate. If the trace comes from a response, it constitutes primary reinforcement; if from perception of an extended stimulus, it is classical conditioning. This paper develops simple models of these processes. It premises exponentially decaying traces related to the richness of the environment, and conditioned reinforcement as the average of such traces over the extended stimulus, yielding an almost-hyperbolic function of duration. The models account for some data, and reinforce the theories of other analysts by providing a sufficient account of the provenance of these effects. It leads to a linear relation between sooner and later isopreference delays whose slope depends on sensitivity to reinforcement, and intercept on that and the steepness of the delay gradient. Unlike human prospective judgments, all control is vested in either primary or secondary reinforcement processes; therefore the use of the term discounting, appropriate for humans, may be less descriptive of the behavior of nonverbal organisms. © 2011 Elsevier B.V.

Impulsivity, risk taking, and timing
Ana A. Baumann | Amy L. Odum
This study examined the relations among measures of impulsivity and timing. Impulsivity was assessed using delay and probability discounting, and self-report impulsivity (as measured by the Barratt Impulsiveness Scale; BIS-11). Timing was assessed using temporal perception as measured on a temporal bisection task and time perspective (as measured by the Zimbardo Time Perspective Inventory). One hundred and forty three college students completed these measures in a computer laboratory. The degree of delay discounting was positively correlated with the mean and range of the temporal bisection procedure. The degree of delay and probability discounting were also positively correlated. Self-reported motor impulsiveness on the BIS-11 was positively correlated with present hedonism and negatively correlated with future orientation on the ZTPI. Self-reported non-planning on the BIS-11 was positively correlated with fatalism on the ZTPI. These results show that people who overestimate the passage of time (perceive time as passing more quickly) hold less value in delayed rewards. They also confirm previous results regarding the relation between delay and probability discounting, as well as highlight similarities in self-report measures of impulsivity and time perspective. © 2012 Elsevier B.V.

Christian Rutz | James J H St Clair
New Caledonian (NC) crows Corvus moneduloides are the most prolific avian tool users. In the wild, they use at least three distinct tool types to extract invertebrate prey from deadwood and vegetation, with some of their tools requiring complex manufacture, modification and/or deployment. Experiments with captive-bred, hand-raised NC crows have demonstrated that the species has a strong genetic predisposition for basic tool use and manufacture, suggesting that this behaviour is an evolved adaptation. This view is supported by recent stable-isotope analyses of the diets of wild crows, which revealed that tool use provides access to highly profitable hidden prey, with preliminary data indicating that parents preferentially feed their offspring with tool-derived food. Building on this work, our review examines the possible evolutionary origins of these birds' remarkable tool-use behaviour. Whilst robust comparative analyses are impossible, given the phylogenetic rarity of animal tool use, our examination of a wide range of circumstantial evidence enables a first attempt at reconstructing a plausible evolutionary scenario. We suggest that a common ancestor of NC crows, originating from a (probably) non-tool-using South-East Asian or Australasian crow population, colonised New Caledonia after its last emersion several million years ago. The presence of profitable but out-of-reach food, in combination with a lack of direct competition for these resources, resulted in a vacant woodpecker-like niche. Crows may have possessed certain behavioural and/or morphological features upon their arrival that predisposed them to express tool-use rather than specialised prey-excavation behaviour, although it is possible that woodpecker-like foraging preceded tool use. Low levels of predation risk may have further facilitated tool-use behaviour, by allowing greater expenditure of time and energy on object interaction and exploration, as well as the evolution of a 'slow' life-history, in which prolonged juvenile development enables acquisition of complex behaviours. Intriguingly, humans may well have influenced the evolution of at least some of the species' tool-oriented behaviours, via their possible introduction of candlenut trees together with the beetle larvae that infest them. Research on NC crows' tool-use behaviour in its full ecological context is still in its infancy, and we expect that, as more evidence accumulates, some of our assumptions and predictions will be proved wrong. However, it is clear from our analysis of existing work, and the development of some original ideas, that the unusual evolutionary trajectory of NC crows is probably the consequence of an intricate constellation of interplaying factors. © 2012 Elsevier B.V.

Tim W. Fawcett | John M. McNamara | Alasdair I. Houston
The tendency of animals to seek instant gratification instead of waiting for greater long-term benefits has been described as impatient, impulsive or lacking in self-control. How can we explain the evolution of such seemingly irrational behaviour? Here we analyse optimal behaviour in a variety of simple choice situations involving delayed rewards. We show that preferences for more immediate rewards should depend on a variety of factors, including whether the choice is a one-off or is likely to be repeated, the information the animal has about the continuing availability of the rewards and the opportunity to gain rewards through alternative activities. In contrast to the common assertion that rational animals should devalue delayed rewards exponentially, we find that this pattern of discounting is optimal only under restricted circumstances. We predict preference reversal whenever waiting for delayed rewards entails loss of opportunities elsewhere, but the direction of this reversal depends on whether the animal will face the same choice repeatedly. Finally, we question the ecological relevance of standard laboratory tests for impulsive behaviour, arguing that animals rarely face situations analogous to the self-control paradigm in their natural environment. To understand the evolution of impulsiveness, a more promising strategy would be to identify decision rules that are adaptive in a realistic ecological setting, and examine how these rules determine patterns of behaviour in simultaneous choice tests. © 2011 Elsevier B.V.

Innovation and problem solving: A review of common mechanisms
Andrea S. Griffin | David Guez

Keren Klass | Marina Cords
The presence of unknown dyadic relationships is a common problem in constructing dominance hierarchies for groups of social animals. Although previously acknowledged, the influence of unknown relationships on hierarchy measures like linearity and steepness has not been studied in detail. Using real data-sets from four groups of wild monkeys, we illustrate how unknown relationships affect linearity and steepness of hierarchies and the consistency of rank ordering based on de Vries' I&SI method. Monte Carlo simulations revealed significant negative linear relationships between the proportion of unknown relationships and both linearity and steepness. These simulations over-estimated steepness and linearity indices relative to additional real-data input matrices. Rank orders became inconsistent at 26-38% unknown relationships, depending on the group. Group size and the specific input matrix substantially affected how much unknown relationships influenced steepness and linearity, the values of these indices and the point at which rank order became inconsistent. We recommend caution in characterizing the dominance structure of a group with many unknown relationships, and in drawing conclusions about hierarchy linearity and steepness based on few input matrices, especially if they contain many unknown relationships. Quantitative characterizations of hierarchies are perhaps best viewed as a somewhat fluid range rather than fixed values. © 2011 Elsevier B.V.

Suzanne H. Mitchell
Delay discounting is steeper for individuals who drink heavily or are alcohol dependent, but the reasons for this are unclear. Given the substantial genetic component for alcohol dependence it is not unreasonable to ask whether discounting and alcohol dependence have a genetic relationship. For there to be a genetic relationship, delay discounting must have a genetic component (heritability). A review of the human and animal literature suggests that this is the case. Other literature examining whether discounting is a correlated phenotype in individuals who are genetically predisposed to drink (family history positive individuals and selected lines of rats and mice) is mixed, suggesting that networks of genes are critical for the relationship to be seen. The identities of the genes in this network are not yet known, but research examining polymorphisms associated with differences in discounting is beginning to address this issue. © 2011 Elsevier B.V.

Tracking of food quantity by coyotes (Canis latrans)
Joseph M. Baker | John Shivik | Kerry E. Jordan
Previous studies have demonstrated that Weber's Law mediates quantitative discrimination abilities across various species. Here, we tested coyotes' (Canis latrans) ability to discriminate between various quantities of food and investigated whether this ability conforms to predictions of Weber's Law. We demonstrate herein that coyotes are capable of reliably discriminating large versus small quantities of discrete food items. As predicted by Weber's Law, coyotes' quantitative discrimination abilities are mediated by the ratio between the large and small quantities of food and exhibit scalar variability. Furthermore, in this task coyotes were not discriminating large versus small quantities based on olfactory cues alone. © 2011 Elsevier B.V.

Catalin V. Buhusi | Sorinel A. Oprisan
In most species, interval timing is time-scale invariant: errors in time estimation scale up linearly with the estimated duration. In mammals, time-scale invariance is ubiquitous over behavioral, lesion, and pharmacological manipulations. For example, dopaminergic drugs induce an immediate, whereas cholinergic drugs induce a gradual, scalar change in timing. Behavioral theories posit that time-scale invariance derives from particular computations, rules, or coding schemes. In contrast, we discuss a simple neural circuit, the perceptron, whose output neurons fire in a clockwise fashion based on the pattern of coincidental activation of its input neurons. We show numerically that time-scale invariance emerges spontaneously in a perceptron with realistic neurons, in the presence of noise. Under the assumption that dopaminergic drugs modulate the firing of input neurons, and that cholinergic drugs modulate the memory representation of the criterion time, we show that a perceptron with realistic neurons reproduces the pharmacological clock and memory patterns, and their time-scale invariance, in the presence of noise. These results suggest that rather than being a signature of higher order cognitive processes or specific computations related to timing, time-scale invariance may spontaneously emerge in a massively connected brain from the intrinsic noise of neurons and circuits, thus providing the simplest explanation for the ubiquity of scale invariance of interval timing.This article is part of a Special Issue entitled: SQAB 2012. © 2013 Elsevier B.V.

Siddharth Gaikwad | Adam Stewart | Peter Hart | Keith Wong | Valerie Piet | Jonathan Cachat | Allan V. Kalueff
The zebrafish (Danio rerio) has emerged as a promising model organism for affective or cognitive neuroscience research, and may be useful to study the interplay between memory and anxiety-related states. To assess the effects of acute psychological stress on spatial and cued memory, adult zebrafish were trained in an aquatic plus-maze for 14 days using food bait as a reward. Two ecologically relevant stressors (alarm pheromone or Indian leaf fish exposure) were applied to acutely stress zebrafish immediately prior to the final (testing) trial. Overall, acute single inescapable stress markedly impaired spatial and cued memory in zebrafish plus-maze test, reducing the number of correct arm entries and time spent in the target arm. This observation parallels rodent and clinical literature on memory-impairing effects of acute stress, strongly supporting the utility of zebrafish in neurobehavioral research. © 2011 Elsevier B.V.

Katrina Rodzon | Meredith S. Berry | Amy L. Odum
Different procedures are often used across experiments to estimate the degree of delay discounting, a common measure of impulsivity. In all procedures, participants indicate their choice between a reward available immediately and one available after a delay. The present experiment determined whether there are differences in the degree of discounting for a hypothetical $100 produced by a procedure that titrates the immediate amount (titrating sequence procedure) versus a procedure that presents a fixed sequence of immediate amounts (fixed sequence procedure) using a within-subject design. The adult human participants showed no significant differences in degree of discounting between procedures as assessed by a hyperboloid model and the Area Under the Curve. Furthermore, the Area Under the Curve values from the two procedures showed a strong positive correlation. These findings suggest there may be no systematic difference between the degree of delay discounting as estimated by the titrating sequence and fixed sequence procedures. Given the apparent similarities in the results, it appears researchers may be justified in basing their choice of which procedure to use on convenience. © 2010 Elsevier B.V.

Gabrielle A. Archard | Victoria A. Braithwaite
Aggression is often positively correlated with other behavioural traits such as boldness and activity levels. Comparisons across populations can help to determine factors that promote the evolution of such traits. We quantified these behaviours by testing the responses of wild-caught poeciliid fish, Brachyrhaphis episcopi, to mirror image stimuli. This species occurs in populations that experience either high or low levels of predation pressure. Previous studies have shown that B. episcopi from low predation environments are less bold than those that occur with many predators. We therefore predicted that fish from high predation populations would be more aggressive and more active than fish from low predation populations. However, we found the opposite - low predation fish approached a mirror and a novel object more frequently than high predation fish suggesting that 'boldness' and aggression were higher in low predation populations, and that population-level boldness measures may vary depending on context. When tested individually, low predation fish inspected their mirror image more frequently. Females, but not males, from low predation sites were also more aggressive towards their mirror image. Variation in female aggression may be driven by a trade-off between food availability and predation risk. This suggests that the relationship between aggression and boldness has been shaped by adaptation to environmental conditions, and not genetic constraints. © 2010 Elsevier B.V.

Ryan D. Ward | Eleanor H. Simpson | Eric R. Kandel | Peter D. Balsam

Zebra finches are bolder in an asocial, rather than social, context
Mark C. Mainwaring | Jessica L. Beal | Ian R. Hartley
Despite an expanding interest in animal personalities, the influence of social interactions and sex differences on individual differences in behaviour remains poorly understood. Using the social zebra finch (Taeniopygia guttata), we tested for behavioural differences in exploration of a novel environment and objects, between individuals of both sexes in relation to a social context; the presence of three male companions, three female companions or no companion birds. We predicted that the presence of conspecific companions should result in focal birds reacting to novelty by exploring more extensively because the companion birds contribute to anti-predator vigilance behaviour and because social isolation often causes behavioural inhibition in social species. We found that exploratory behaviour of focal individuals was significantly reduced in the presence of conspecific companions, irrespective of the companion's sex. Moreover, we found a weak trend towards females being more exploratory than males, irrespective of the social context. These results demonstrate the importance of considering the social context in animal personality studies and of exploring sex differences in personalities. © 2011 Elsevier B.V.

William J. Matthews
Behavioural timing is frequently assumed to be based on the accumulation of pulses from a pacemaker. In humans, verbal estimation is often used to determine whether the effect of factors which influence subjective time become more pronounced at longer durations - that is, if they affect the slope of the judgment function, consistent with a change in the rate of the pacemaker. Here, participants judged blank intervals marked by two squares which either did or did not differ in size. In Experiment 1, a small change in marker size produced shorter temporal judgments than a large change. This effect was independent of objective duration and indicates that the slope changes seen in previous work are not an inevitable artefact of the verbal estimation procedure. However, Experiments 2 and 3 included conditions where the markers did not change size and established (a) that the effect of marker size depends on the other stimuli presented during the experiment, and (b) that slope effects occur even when they cannot possibly be due to a change in the rate of the pacemaker. Taken together, these results urge some caution in the use of verbal estimation as a methodology for deconstructing the putative internal clock. © 2010 Elsevier B.V.


Affirmations Are Positive Statements

The subconscious mind is like a great and wonderful computer, and affirmations are the commands that program it to act in the way you choose. If you feed it with negative thoughts and words, the mind will produce negative conditions, but if you feed it with positive thoughts and words it will produce positive conditions and circumstances.

There is no magic or supernatural powers involved here. By repeating affirmations, you are focusing on a certain thought over and over again, which ultimately sinks into your subconscious mind, and then you will consciously and subconsciously always carry this thought with you, and be moved and motivated to make it come true. You will get ideas and intuition, see and be aware of opportunities and get help from others to make what you affirm come tue.

AffirmationsThere are several ways to repeat affirmations, and there are certain mental laws to follow in order to get results.

There is much more to it than just repeating words, and this why I have written a special book about affirmations, with all the necessary information, instructions and guidance. It also includes lists of affirmations for almost every goal or situation. It is a complete course and workbook for affirmations, and is called Affirmations – Words with power. You can learn all about it by clicking here.About the Author

Remez Sasson

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CHILDREN swapped their classroom for the supermarket aisle on a visit to Tesco Extra in Stockton to take part in a Farm To Fork Trail, in a quest to find out more about the food on their plate and how it gets there.

Backed by Diabetes UK, the Children’s Food Trust and the NFU amongst others, Farm To Fork is the first initiative of Tesco’s Eat Happy Project, a major new food education programme that is committed to improving children’s relationship with food.

Farm To Fork will see food suppliers across the country opening their farms and factories to teach children how, for example, milk is produced, where eggs come from and how lettuce grows. Specially trained colleagues in more than 700 Tesco stores across the UK will also be teaching children about different foods and giving practical demonstrations, for example, baking bread, tasting new fruits and vegetables and learning all about fish.

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Tesco’s ambition is to give one every primary school in the UK opportunity to go on the trails, to support their syllabus in learning about food, farming and nutrition.

On their trail, pupils aged five and six, from Harrow Gate Primary School were treated to an interactive learning session behind the scenes at the Tesco store to see first-hand and learn up close how some of the food they eat makes it way to their plate. The children were offered different activities in all the major departments such as the produce department and the cheese counter, where they were given an opportunity to try a piece of fruit or cheese they have never eaten before.


I noticed that AsyncQueryRunner duplicates much of the code from QueryRunner. Would it be possible for AsyncQueryRunner to simply decorate a QueryRunner with async functionality? For example, pass in a QueryRunner instance in the constructor and delegate the methods to it. This would reduce the amount of code duplication and ease future API extensions. Are there issues I'm overlooking? Moandji


An LDS is not just an information technology (IT) project

An LDS is not just an IT project.
An LDS is a business solution, a way to meet information needs. IT staff can build an LDS, but the system they develop may not meet user needs. Education experts and other data users must work closely with IT throughout the design and development process to ensure the system will effectively serve their requirements. Developers must consider how users do their jobs and what functionalities will make this work easier and more efficient. They should also think about how end users will access and use the data and how the new system can help them maximize the information's utility.

moon icon "We'll just buy an LDS and be done with it."


Assets are reported on the balance sheet usually at cost or lower. Assets are also part of the accounting equation: Assets = Liabilities + Owner's (Stockholders') Equity.

Some valuable items that cannot be measured and expressed in dollars include the company's outstanding reputation, its customer base, the value of successful consumer brands, and its management team. As a result these items are not reported among the assets appearing on the balance sheet.