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For some years now I have made occasional mention of a survey conducted in May 2013 to March 2014 to find out what intelligence researchers thought about racial differences in intelligence. Now the paper has been published, so in academic terms the work actually exists, and can be quoted and commented upon. I can remember looking at the draft of this survey, suggesting it be made shorter, which is what I always say. Long surveys lead to low return rates. When it finally came out, I’m not sure exactly how I answered it, but will give my best recollections in this post. Academia makes a tradition out of slowness: the last survey on this matter was in 1988. By this reckoning the next survey will be in 2052. No need to rush things.

Survey of expert opinion on intelligence: Intelligence research, experts’ background, controversial issues, and the media. Heiner Rindermann, David Becker, Thomas R. Coyle. Intelligence 78 (2020) 101406
https://doi.org/10.1016/j.intell.2019.101406

Abstract
Experts (N max = 102 answering) on intelligence completed a survey about IQ research, controversies, and the media. The survey was conducted in 2013 and 2014 using the Internet-based Expert Questionnaire on Cognitive Ability (EQCA). In the current study, we examined the background of the experts (e.g., nationality, gender, religion, and political orientation) and their positions on intelligence research, controversial issues, and the media. Most experts were male (83%) and from Western countries (90%). Political affiliations ranged from the left (liberal, 54%) to the right (conservative, 24%), with more extreme responses within the left-liberal spectrum. Experts rated the media and public debates as far below adequate. Experts with a left (liberal, progressive) political orientation were more likely to have positive views of the media (around r= |.30|). In contrast, compared to female and left (liberal) experts, male and right (conservative) experts were more likely to endorse the validity of IQ testing (correlations with gender, politics: r= .55, .41), the g factor theory of intelligence (r= .18, .34), and the impact of genes on US Black-White differences (r= .50, .48). The paper compares the results to those of prior expert surveys and discusses the role of experts’ backgrounds, with a focus on political orientation and gender. An underrepresentation of viewpoints associated with experts’ background characteristics (i.e., political views, gender) may distort research findings and should be addressed in higher education policy.

As you can see, the paper confronts the politics/attitudes nexus head on. The popular view is that political orientations determine attitudes to scientific findings: find the author’s politics and you can predict and also discount their opinions. On the contrary, author’s observations of life may determine their politics, and in fairness you can equally argue that once you find the author’s observations and experiences you should discount their politics.

Who were the experts?

The survey was sent to authors who published at least one article after 2010 in journals covering cognitive ability. The journals included Intelligence, Cognitive Psychology, Contemporary Educational Psychology, New Ideas in Psychology, and Learning and Individual Differences. In addition, members of the International Society for Intelligence Research (ISIR) were invited (from December 2013 toJanuary 2014) to complete the EQCA, and an announcement was published on the website of the International Society for the Study of Individual Differences (ISSID).

A total of 265 responses were received, which produced a response rate of 19.71% from those approached for an opinion. This is not very good. The survey was long, which may have put people off, and since it asked about contentious matters, experts may have felt it was best avoided. As you may note later below, less than half of those who replied answered the item on racial differences in intelligence. They may have worried that the personal responses would leak out in some way.

The respondents have a claim to expertise. Their academic work was better than the scholarly average, so they probably know their subject. They were somewhat Left inclined, and this had an impact on questions like the contribution genetics makes to black-white differences. 16% of experts reported a 100% environmental explanation, whereas 6% reported a 100% genetic explanation. This group leans left in general, and is more extremely left on this particular issue. (For the record, I find it hard to argue for either of these extreme positions. My recollection is that I was in the 50:50 camp). Psychologists are generally very Left inclined, and intelligence researchers somewhat Left inclined.

According to Duarte et al. (2015, their Fig. 1), the leftward tilt in psychology emerged over the last three decades, leading to a 14:1 ratio of left (progressive, democratic) to right (conservative, republican) psychology faculty. More recent data show an even larger disparity (16.8:1, Langbert, 2018). The leftward drift is reinforced by a liberal bias among journalists (e.g., Groseclose & Milyo, 2005; Kuypers, 2002; Lichter, Rothman, & Lichter, 1986) and in Wikipedia (e.g., Greenstein & Zhu, 2012, 2018). In addition, there have been increasing disruptions and attacks against scientists with a perceived right orientation at university talks (e.g., Duarte et al., 2015; HXA Executive Team et al., 2018; Inbar & Lammers, 2012; Jussim, 2018). Student groups have interrupted lectures, courses, and invited talks, and in some cases violently attacked scientists and scholars with a perceived right orientation (e.g., Charles Murray; Arm, 2016; Beinart, 2017). Finally, these events parallel a growing political divide between progressive and conservative factions in the US and other countries (Pew Research Center, 2017, p. 7f.). In the Pew survey, the gap between Democrats and Republicans in the US grew (in 10 political domains) from an average of 14.9% in 1994 to 35.8% in 2017, an increase of 20.9%. 20.8% of this increase (or 99.5% of the growth) was due to a shift to the left by Democrats, whereas 0.1% was due to a shift to the right by Republicans.

Of course, if our science is worth anything, none of this should matter. Leftists should follow the facts, and where the weight of evidence supports a conclusion, they should back that conclusion. Rightists should likewise follow the evidence. As James Flynn says, science should be allowed to do its work.

Respondents are not very religious, but are socially liberal, and lean Left.


Rinderman et al. worry that

Political bias impacts selection of research topics, decisions by Institutional Review Boards (IRBs) to perform studies, funding of studies, interpretation of research, publication of research, reception and citation of studies, and promotion of researchers, all of which distorts the scientific process and perceptions about science. Jussim described such bias for the specific example of research on stereotypes resulting in limited support for research on stereotype accuracy, which usually confirms the accuracy of stereotypes about group differences. Despite receiving limited attention in science and the media, stereotype accuracy has been replicated in independent studies, reported in preregistered studies, and published in diverse outlets (e.g., Ashton & Esses, 1999; Johnson & Wilson, 2019; Jussim, 2012; Kirkegaard & Bjerrekær, 2016).

In other words, psychologists are against public attitudes they classify as being biased stereotypes. They are less keen to admit that many stereotypes are probably true, and well supported by evidence. They have a bias to show that members of the public are biased, even when they are simply observing actual differences between people. This is an example of a bias within psychological research. I agree that this is the case, and that it is lamentable, but I don’t think that the answer lies in getting more Conservatives into psychology. People should be free to choose their occupations.

In the original survey, Snyderman and Rothman (1988) found that journalists were more likely than experts to favour non-genetic explanations, endorse test bias, and identify with the political left. 76% of science magazine editors identified as extremely or very liberal, compared to 45% of journalists and 32% of intelligence experts. This suggests that Left leaning psychologists (the majority) find their conclusions get a better reception and more publicity from Left leaning science reporters (the majority).

Experts differed according to their backgrounds as to how they rated social and political issues:

Compared to right-conservative experts, left-progressive experts favored a specific abilities perspective, favored environmental explanations for Black-White IQ gaps, assumed more bias in testing, and were against IQ in immigration policies. In contrast, experts with a right-conservative perspective showed a “right tilt,” which was associated with the opposite pattern (i.e., favoring the g factor, favoring genetic explanations for Black-White IQ gaps, assuming less bias in testing, favoring IQ in immigration policies).
[]
In sum, the political orientation and gender of experts were the most important factors in explaining the observed (but not always large) heterogeneity among expert opinions on intelligence research.

Experts believe that research should be published, not suppressed to gain peace and quiet. They value the work of Carroll, Bouchard, Deary, Jensen and Plomin.

The allegation that people hold a particular view about the genetics of intelligence merely because, say, they are old, conservative men is, by that token, refuted because the objection comes from, say, young, liberal women. This line of argument gets nowhere, since it assumes that personal identity is all, that facts don’t matter, indeed, that there are no facts other than those created by persons with different attitudes (some reprehensible, some desirable). On this argument, we cannot tell what can be seen through a telescope until we can see into the political minds of the astronomers. A contrary view is that better methods lead to better measures, shown to be so by lower errors and by reproducible results. Like Einstein, we should always be proposing ways in which our theories could be proven wrong.

Rinderman et al. are not downcast. They note that when the research literature is fairly clear, then there is general agreement.

In the current study, questions with clear empirical results (in the scientific literature) generally yielded similar answers for males and females, whose opinions were consistent with the scientific literature (e.g., few reports of IQ test bias). In contrast, intelligence research yields more ambiguous results for other research questions, which have no clear answers in the scientific literature (e.g., group differences in heritability). Such questions generally showed more variability in EQCA responses, including differences between males and females on the heritability of US White-Black IQ differences.

For example, the g model of intelligence was backed by 58% of experts in 1988 and by 76% of experts in 2014.

Have opinions about racial differences changed since 1988? In those 26 years there has been an increase in the willingness to ascribe intelligence differences to genetic causes.

You will see that there are some hardliners who believe that black/white differences are entirely environmental, and some (fewer) hardliners who who believe them to be entirely genetic in origin. There are peaks at 50% and 80%. The 50:50 judgment is a popular compromise. The 80% figure is more interesting, because it was the percentage that Jensen (and Rushton) inclined towards in their 2005 review of the literature, or at least mentioned as being possible. Some researchers may regard this as a prediction.

A controversial topic is the cause of past and current US Black-White differences in IQ test results. In the IQSC survey (Snyderman & Rothman, 1988), a plurality (45%) of experts noted the influence of both genetic and environmental factors. In contrast, monocausal positions (i.e., genetic or environmental) were rare but were much more likely to be environmental (15%) than genetic (1%; Snyderman & Rothman, 1988, p. 128). In the current study, EQCA experts were asked what percentage of the US Black-White differences in IQ is, in their view, due to environment or genes. In general, EQCA experts gave a 50–50 (50% genes, 50% environment) response with a slight tilt to the environmental position (51% vs. 49%; Table 3). When EQCA experts were classified into discrete categories (genetic, environmental, or 50–50), 40% favored an environmental position, 43% a genetic position, and 17% assumed 50–50. The difference in the average versus discrete results may seem contradictory (average results tilted to the environment and discrete categories tilted to genes), except when extreme positions are considered. 16% of experts who favored an environmental perspective assumed a 100% environmental position, whereas only 6% of experts who favored a genetic perspective assumed a 100% genetic position (Fig. 3). That is, the opinion of “environmentalists” was more extreme than the opinion of “geneticists.”

There has been some progress, in the sense that more experts are willing to agree that genetics is involved in the intellectual differences between genetic groups. The most extreme position, in the sense of experts betting the house on an extreme judgment, is held by environmentalists. I can’t see how either extreme position could be held, but will listen to the arguments as more data come in.

This is a good study which reveals important findings about contentious subjects. If it was to be done again, I would make the survey far shorter, repeating the key questions, and ensuring that respondents were allowed different options to anonymize their responses, in addition to the anonymization offered by the authors of the study. I would also hope that it would be published soon after the data having been collected. However, academic life is full of demands, and not every piece of research can reach the public promptly. Roll on 2052.

 
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