Rindermanna, Becker, and Coyle. “Survey of expert opinion on intelligence: Intelligence research, experts’ background, controversial issues, and the media” (2020).
This sociology-of-science study is fascinating, filled with gems, and provides numerous promising roads for further research. Among those surveyed, the g-factor model of intelligence (vs the ‘specific abilities model’) is the dominant view, quite amazing given how the field of psychology is, overall, very left-wing.
Some choice quotes:
- “16% of experts favored a specific abilities perspective (1–4), whereas 76% favored a general factor perspective (6–9; 8% scale average 5). There was little to no support for separate subgroup norms for different racial, ethnic, or social groups or for people with different nationalities (natives vs. immigrants), with the percentage of experts favoring separate norms below 25%.”
- “Experts attributed nearly half of the Black-White difference to genetic factors, with 51% attributing the difference to environmental factors and 49% to genetic factors.”
- “Experts believed 45% of SES variance was explained by intelligence and 55% by non-IQ factors (Table 3). 51% of experts believed that the contribution of intelligence (to SES) was below 50%, 38% above 50%, and 12% had a 50–50 opinion.”
- Compared to males, females (N = 12, 17%, vs. male N = 60, 83%) were somewhat more likely to have a “progressive” or “left” perspective (Table 6), favoring a specific abilities view rather than a g factor view (r = .19, d = 0.52). 2 Females were also more likely than males to favor separate test norms for different ethnic, racial, national, and social groups (rs = −.12 to −.37), 3 and to endorse an environmental (rather than genetic) view of US White-Black IQ differences(r = .48, d = 1.29; males 61% heritability vs. females 23%). Finally, females were more likely to assume bias in cognitive testing (rs = −.21 to −.49) and less likely to favor cognitive testing in immigration decisions (r = .43, d = 1.14; on a scale from 1 to 9, males M M = 5.67, SD M = 3.14, and females M F = 2.00, SD F = 1.34). Female experts were younger than male experts (r = .29, M M = 50.90 years, SD M = 14.86, and M F = 39.50, SD F = 9.89).
- “46% of the experts argued against the use of IQ in immigration policy, whereas 48% argued in favor of its use.”
- “A small number of experts declined to work with the media.” (Which way do you think *they* lean politically? – LM)
- “Left experts were more likely to report positive experiences with the media and in public debates, while right experts were more likely to report problems in publishing research.”
- “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).”
- “It could be argued that science should be oriented toward epistemic rationality, i.e., toward reasonable and well-founded methods and truth, and that other issues such as political orientation or gender representation are not important. However, as noted by Duarte et al. (2015), the current imbalance of political orientations in psychology can undermine the quality of psychological research. Possible consequences comprise political bias in all stages of research. Examples are given by Buss and von Hippel (2018), Ceci and Williams (2020), Jussim (2012), and Stevens et al. (2018): 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).”
