1. In 2003, Kahneman published an article in American Psychologist describing the magic of collaborating with Tversky but also lamenting how current modes of scientific disagreement were unnecessarily hostile and unproductive. He hoped for a better way: Adversarial Collaborations

2. 21 years later, these procedures remain rare. Ceci, Williams, @PsychRabble and I just published an article (also in American Psychologist) explaining why ACs are needed to improve scientific outputs and restore credibility to behavioral science: psycnet.apa.org/doiLanding?doi…

1. Hot off the press: Taboos & Self-Censorship

In a sample of psych profs, we identify points of conflict & consensus regarding (1) controversial empirical claims & (2) normative preferences for how controversial scholarship & scholars should be treated: journals.sagepub.com/doi/full/10.11… 2. Off-limits research conclusions tend to involve group differences in socially important outcomes, and particularly when differences are attributed to genetic or otherwise natural differences between groups (as opposed to social or environmental causes).

1. My latest now out in @PNASNews w/38 all-star co-authors. Scientists censor themselves and each other largely for prosocial reasons, to protect reputations from public scrutiny & to protect vulnerable groups from potentially harmful scientific findings: pnas.org/doi/10.1073/pn… 2. However these harm concerns are largely based on intuitive assumptions rather than empirical evidence, and the immediate and downstream costs of censorship are rarely weighed against the supposed harms.

1. New meta-analysis of 85 studies testing gender bias in hiring practices & forecasting surveys asking scientists & laypeople to predict the results found:

-Post-2009, hiring biases favor females
-Scientists & laypeople wildly overestimate gender bias
sciencedirect.com/science/articl… 2. This meta included 44 years of field audit studies (in which carefully-matched female & male job applications are sent to real orgs) testing for gender biases in callback rates for female-
stereotypical, gender neutral, & male-stereotypical jobs

1. Science journals have begun adding moral criteria to their pub guidelines, stating they might reject or retract potentially harmful papers.

In 2 studies, Maja Graso @irakresh @PTetlock & I found that people systematically overestimate scientific harms:
journals.sagepub.com/doi/abs/10.117… 2. Subjects read summaries of 6 potentially controversial findings (e.g., that female mentees benefit when they have more male than female mentors). One group reported whether they support various behavioral reactions. The other estimated the % of people who support each reaction

1. Even when ideologies align, people distrust politicized institutions:

In 3 studies & across 40 institutions, @calvinisch2 @JimACEverett @azimshariff & I find evidence that perceived politicization is strongly associated with lower trust in institutions
https://t.co/aYts6O1h1Qpsyarxiv.com/sfubr
2. This was observed on an individual difference level: When people perceived institutions as politicized, they trusted them less.

& This was observed between institutions: Institutions perceived as the most politicized were also the least trusted, with a large effect, r = -0.76

1. Academia increasingly prioritizes equity and works to ensure scholarship does not offend or pose risks to vulnerable groups. @EPoe187 and I contend that these shifting priorities are caused, in part, by the growing proportion of women in academia:
quillette.com/2022/10/08/sex… 2. A few points of evidence:
Over the past few decades, women increasingly earn higher proportions of doctoral degrees and faculty positions in higher education

1. Science often contradicts other science. When this happens, disputant scholars tend to work separately, designing their own new studies to launch at their opponents. These new studies rarely persuade the other side, and contradictory claims live in on for years or decades. 2. On rare occasions, scholars swallow their pride and put their theories at real risk by working with their intellectual opponents. These are called Adversarial Collaborations (term coined by Danny Kahneman), and @PTetlock and I have been working hard to normalize them.

1. In my new chapter w/@natehoneycutt & @PsychRabble, we argue that scientists might actually be humans. And that as humans, scientists might be vulnerable to the same kinds of errors, biases, & motivations that they so often study in non-scientist humans:
researchgate.net/publication/34… 2. We suggest that scientists might occasionally engage in motivated research: Their own human desires might influence how they familiarize themselves with data, collect and analyze observations, draw and describe conclusions, and evaluate their peers' research.

1. A sneak peak at yet unpublished meta-analyses on whether there is gender bias in academic science in six domains: letters of recommendation, tenure-track hiring, journal acceptances, grant funding, salary, and teaching ratings:

journals.sagepub.com/doi/full/10.11… 2. In teaching evaluations, female instructors are rated lower than male instructors by both male and female students. So some evidence of gender bias there (although it would be helpful to know whether this finding holds up when gender is experimentally manipulated).

1. Here's a New Year's Resolution: More tolerance toward political opponents🥳

Dems and Reps tend to caricature one another (see example below from perceptiongap.us)

Our opponents really are not as extreme, homogeneous, or morally inferior as people tend to think. 2. These caricatures or 'perception gaps' are lowest among more moderate people and increase as people are more politically extreme. Which suggests that people who have more accurate views of the political landscape tend not to be extremists.