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Political Bias in the Social Sciences: A Critical, Theoretical, and Empirical Review
Abstract
This chapter is a critical, theoretical, and empirical review of political bias. It is “critical” in that it roundly criticizes the manner in which the social sciences have allowed political biases to undercut the validity and credibility of their scholarship. It is a theoretical review because the chapter presents two complementary and synergistic models of academic bias (one about its manifestations, the other about its processes). It is empirical because the chapter then uses those models to review the now vast evidentiary case for political bias, and because this chapter presents new data providing further evidence of such biases. This chapter also highlights when proposed manifestations of political bias are plausible but not yet demonstrated – thereby also identifying potential directions for future empirical research.
... Those who argue that a repressive climate exists within academia have a tendency to apply the birthright principle specically to tenured academics, whose speech they defend vigorously without regard to its content, yet the same proponents will deride lesser mortals (who have access to social media but not to academic journals) as "vigilantes" or "mobs". 24,[26][27][28][29][30][31][32][33][34][36][37][38] This kind of tone policing, 153,154 in which a critique of the emotionality of an argument is used to deect discussion of its substance, has long been used to silence marginalized voices. ...
... 520 His rants against a "radical vigilante woke mob" 521,522 are indistinguishable (to my ears) from the language used by academics who defend birthright speech. [24][25][26][27][29][30][31][32][33][34][35][36][37][38] Whereas the latter group's premise is that academics are devouring their own academic freedom, these examples encapsulate how catchphrases such as "woke identity" and "woke activism" are in fact used by politicians as a pretense to restrict speech, under the guise of a crusade against a purportedly anti-speech "cancel culture". [523][524][525][526][527][528] It is these restrictions, rather than squabbles about offensive remarks by this or that academic, that are having a real impact on academic freedom. ...
... 599 They also experience homelessness at far higher rates. 600,601 Transphobia has become a point of xation for the birthright-speech community, [30][31][32]36,37 which has once again attempted to disguise bigotry under a patina of academic freedom. 30,[602][603][604][605][606][607][608][609][610][611][612] One example is a controversial study of "rapidonset gender dysphoria", 613 a pseudoscientic term invented and weaponized by the trans-antagonistic community. ...
A vocal group of academic scientists have repeatedly articulated the idea that academic freedom is under attack from within academia. Examples of supposed suppression of free expression often involve diversity,...
... One possibility is that the community of researcher-activists do not really want to understand the world-they want to change it. Their conclusions are designed to support an ideologically left sociopolitical narrative rather than advance science (Crawford & Jussim, 2018;Honeycutt & Jussim, 2022). It is sobering to think of how much scientific progress has been impeded, and how much time has been wasted, by a lack of skepticism in this area. ...
Schein (1973) is a highly cited article in research on sex and gender biases. The original article concluded that people are biased against women regarding requisite management characteristics. However, the present paper replicates Schein (1973) and demonstrates that the findings were a result of an imbalanced ratio of items which exhibited mean differences between men and women targets. In addition, the use of intraclass correlations creates an illusion of large differences or similarities between targets when the actual mean rating differences are practically trivial and statistically nonsignificant. A bias against women, against men, and no bias are obtained by altering the number of male and female items, or by applying the intraclass correlation to more appropriate data. The implications of the results for the measurement of sex and gender biases are discussed. Broader concerns are raised about ideological biases which allow for conclusions and theories to propagate without empirical support.
In recent years, the veracity of scientific findings has come under intense scrutiny in what has been called the “replication crisis.” This crisis is marked by the propagation of scientific claims which were subsequently contested, found to be exaggerated, or deemed false. This article describes the replication crisis and identifies examples of unreproducible results and irreplicable findings from across the biomedical and social sciences. Purported causes and potential remedies to the crisis are examined. It is argued that social work research suffers from the many analytic and methodological vices described here and that the profession is likely in crisis itself. Consequences for the discipline, as both a research and practice-based profession, are explored and paths forward are proposed.
Authoritarianism has been the subject of scientific inquiry for nearly a century, yet the vast majority of authoritarianism research has focused on right-wing authoritarianism. In the present studies, we investigate the nature, structure, and nomological network of left-wing authoritarianism (LWA), a construct famously known as “the Loch Ness Monster” of political psychology. We iteratively construct a measure and data-driven conceptualization of LWA across six samples (N = 7,258) and conduct quantitative tests of LWA’s relations with more than 60 authoritarianism-related variables. We find that LWA, right-wing authoritarianism, and social dominance orientation reflect a shared constellation of personality traits, cognitive features, beliefs, and motivational values that might be considered the “heart” of authoritarianism. Relative to right-wing authoritarians, left-wing authoritarians were lower in dogmatism and cognitive rigidity, higher in negative emotionality, and expressed stronger support for a political system with substantial centralized state control. Our results also indicate that LWA powerfully predicts behavioral aggression and is strongly correlated with participation in political violence. We conclude that a movement away from exclusively right-wing conceptualizations of authoritarianism may be required to illuminate authoritarianism’s central features, conceptual breadth, and psychological appeal. (PsycInfo Database Record (c) 2021 APA, all rights reserved)
Selectively publishing results that support the tested hypotheses (“positive” results) distorts the available evidence for scientific claims. For the past decade, psychological scientists have been increasingly concerned about the degree of such distortion in their literature. A new publication format has been developed to prevent selective reporting: In Registered Reports (RRs), peer review and the decision to publish take place before results are known. We compared the results in published RRs ( N = 71 as of November 2018) with a random sample of hypothesis-testing studies from the standard literature ( N = 152) in psychology. Analyzing the first hypothesis of each article, we found 96% positive results in standard reports but only 44% positive results in RRs. We discuss possible explanations for this large difference and suggest that a plausible factor is the reduction of publication bias and/or Type I error inflation in the RR literature.
This paper explores the suppression of ideas within an academic scholarship by academics, either by self-suppression or because of the efforts of other academics. Legal, moral, and social issues distinguishing freedom of speech, freedom of inquiry, and academic freedom are reviewed. How these freedoms and protections can come into tension is then explored by an analysis of denunciation mobs that exercise their legal free speech rights to call for punishing scholars who express ideas they disapprove of and condemn. When successful, these efforts, which constitute legally protected speech, will suppress certain ideas. Real-world examples over the past five years of academics that have been sanctioned or terminated for scholarship targeted by a denunciation mob are then explored.
Social science researchers are predominantly liberal, and critics have argued this representation may reduce the robustness of research by embedding liberal values into the research process. In an adversarial collaboration, we examined whether the political slant of research findings in psychology is associated with lower rates of scientific replicability. We analyzed 194 original psychology articles reporting studies that had been subject to a later replication attempt ( N = 1,331,413 participants across replications) by having psychology doctoral students (Study 1) and an online sample of U.S. residents (Study 2) from across the political spectrum code the political slant (liberal vs. conservative) of the original research abstracts. The methods and analyses were preregistered. In both studies, the liberal or conservative slant of the original research was not associated with whether the results were successfully replicated. The results remained consistent regardless of the ideology of the coder. Political slant was unrelated to both subsequent citation patterns and the original study’s effect size and not consistently related to the original study’s sample size. However, we found modest evidence that research with greater political slant—whether liberal or conservative—was less replicable, whereas statistical robustness consistently predicted replication success. We discuss the implications for social science, politics, and replicability.
For more than twenty-five years implicit measures have shaped research, theorizing, and
intervention in psychological science. During this period, the development and deployment of implicit measures have been predicated on a number of theoretical, methodological, and applied assumptions. Yet these assumptions are frequently violated and rarely met. As a result, the merit of research using implicit measures has increasingly been cast into doubt. In this paper, we argue that future implicit measure research could benefit from adherence to four guidelines based on a functional approach wherein performance on implicit measures is described and analyzed as behavior emitted under specific conditions and captured in a specific measurement context. We unpack this approach and highlight recent work illustrating both its theoretical and practical value.
This article provides a comprehensive review of divergent conceptualizations of the "implicit" construct that have emerged in attitude research over the past two decades. In doing so, our goal is to raise awareness of the harmful consequences of conceptual ambiguities associated with this terminology. We identify three main conceptualizations of the "implicitness" construct: The procedural conceptualization (implicit as indirect), the functional conceptualization (implicit as automatic), and the mental theory conceptualization (implicit as associative), as well as two hybrid conceptualizations (implicit as indirect and automatic, implicit as driven by affective gut reactions). We discuss critical limitations associated with each conceptualization and explain that confusion also arises from their coexistence. We recommend discontinuing the usage of the "implicit" terminology in attitude research and research inspired by it. We offer terminological alternatives aimed at increasing both the precision of theorization and the practical value of future research.
We argue that because of a long history of intergroup conflict and competition, humans evolved to be tribal creatures. Tribalism is not inherently bad, but it can lead to ideological thinking and sacred values that distort cognitive processing of putatively objective information in ways that affirm and strengthen the views and well-being of one’s ingroup (and that increase one’s own standing within one’s ingroup). Because of this shared evolutionary history of intergroup conflict, liberals and conservatives likely share the same underlying tribal psychology, which creates the potential for ideologically distorted information processing. Over the past several decades, social scientists have sedulously documented various tribal and ideological psychological tendencies on the political right, and more recent work has documented similar tendencies on the political left. We contend that these tribal tendencies and propensities can lead to ideologically distorted information processing in any group. And this ideological epistemology can become especially problematic for the pursuit of the truth when groups are ideologically homogenous and hold sacred values that might be contradicted by empirical inquiry. Evidence suggests that these conditions might hold for modern social science; therefore, we conclude by exploring potential ideologically driven distortions in the social sciences.
A crescendo of incidents have raised concerns about whether scientific practices in psychology may be suboptimal, sometimes leading to the publication, dissemination, and application of unreliable or misinterpreted findings. Psychology has been a leader in identifying possibly suboptimal practices and proposing reforms that might enhance the efficiency of the scientific process and the publication of robust evidence and interpretations. To help shape future efforts, this paper offers a model of the psychological and socio-structural forces and processes that may influence scientists' practices. The model identifies practices targeted by interventions and reforms, and which practices remain unaddressed. The model also suggests directions for empirical research to assess how best to enhance the effectiveness of psychological inquiry.
The effects of gender stereotype threat on mathematical test performance in the classroom have been extensively studied in several cultural contexts. Theory predicts that stereotype threat lowers girls’ performance on mathematics tests, while leaving boys’ math performance unaffected. We conducted a large-scale stereotype threat experiment in Dutch high schools (N = 2064) to study the generalizability of the effect. In this registered report, we set out to replicate the overall effect among female high school students and to study four core theoretical moderators, namely domain identification, gender identification, math anxiety, and test difficulty. Among the girls, we found neither an overall effect of stereotype threat on math performance, nor any moderated stereotype threat effects. Most variance in math performance was explained by gender, domain identification, and math identification. We discuss several theoretical and statistical explanations for these findings. Our results are limited to the studied population (i.e. Dutch high school students, age 13–14) and the studied domain (mathematics).
SCIENTIFIC In this article, we argue that there are many unanswered questions crucial to scientific understanding about stereotypes and stereotype accuracy. We present a review and analysis suggesting that a set of cognitive, motivational, and social factors conspired to prevent psychologists from asking serious questions about stereotype accuracy for decades and may help explain why many reviews in the field foreclose on presumptive answers to questions that actually require empirical data. We review the history of the first unasked question in this area, “Are stereotypes inaccurate?” which went unaddressed for about 70 years after the initial social science interest in stereotypes. Current unasked questions include (a) When and how does relying on a stereotype increase the accuracy of person perception? (b) Why are some stereotypes more accurate than others? (c) How accurate are implicit stereotypes? (d) Do people ever actually ignore individuating information? We conclude with testable hypotheses about the sources of not asking certain questions, and with recommendations for overcoming biases and blind spots in research on stereotypes.
SCIENTIFIC In this paper, we argue that four interlocking barriers beset psychologists seeking to develop a proper science of social psychology. The first is the ideological orientation characteristic of most social psychologists—heavily skewed on the left side of the political spectrum. The second is the adoption of a view of human nature that social psychologists believe to be most conducive to that ideology—a blank slate that is corrupted solely by the ills of bad environments. The third is a rejection of theories and findings believed to contravene that view of human nature—those coming from evolutionary approaches to human behavior. The fourth is a suite of evolved psychological adaptations that actively impede an understanding of evolutionary psychology—adaptations for social persuasion rather than truth-seeking, adaptations for prestige maintenance, and adaptations for forming and maintaining in-group coalitions and for punishing competing coalitions. We examine these scientific impediments with empirical data based on a survey of 335 established social psychologists from the premier scientific society, The Society for Experimental Social Psychology (SESP). We conclude with the irony that our evolved psychology may interfere with the scientific understanding of our evolved psychology.
The present investigation provides the first systematic empirical tests for the role of politics in academic research. In a large sample of scientific abstracts from the field of social psychology, we find both evaluative differences, such that conservatives are described more negatively than liberals, and explanatory differences, such that conservatism is more likely to be the focus of explanation than liberalism. In light of the ongoing debate about politicized science, a forecasting survey permitted scientists to state a priori empirical predictions about the results, and then change their beliefs in light of the evidence. Participating scientists accurately predicted the direction of both the evaluative and explanatory differences, but at the same time significantly overestimated both effect sizes. Scientists also updated their broader beliefs about political bias in response to the empirical results, providing a model for addressing divisive scientific controversies across fields.
On political questions, many people prefer to consult and learn from those whose political views are similar to their own, thus creating a risk of echo chambers or information cocoons. We test whether the tendency to prefer knowledge from the politically like-minded generalizes to domains that have nothing to do with politics, even when evidence indicates that politically like-minded people are less skilled in those domains than people with dissimilar political views. Participants had multiple opportunities to learn about others’ (1) political opinions and (2) ability to categorize geometric shapes. They then decided to whom to turn for advice when solving an incentivized shape categorization task. We find that participants falsely concluded that politically like-minded others were better at categorizing shapes and thus chose to hear from them. Participants were also more influenced by politically like-minded others, even when they had good reason not to be. These results replicate in two independent samples. The findings demonstrate that knowing about others’ political views interferes with the ability to learn about their competency in unrelated tasks, leading to suboptimal information-seeking decisions and errors in judgement. Our findings have implications for political polarization and social learning in the midst of political divisions.
Evidence-based medicine is the cornerstone of clinical practice, but it is dependent on the quality of evidence upon which it is based. Unfortunately, up to half of all randomized controlled trials (RCTs) have never been published, and trials with statistically significant findings are more likely to be published than those without (Dwan et al., 2013). Importantly, negative trials face additional hurdles beyond study publication bias that can result in the disappearance of non-significant results (Boutron et al., 2010; Dwan et al., 2013; Duyx et al., 2017). Here, we analyze the cumulative impact of biases on apparent efficacy, and discuss possible remedies, using the evidence base for two effective treatments for depression: Antidepressants and psychotherapy.
The field of sociology has long been subject to critique for alleged ideological bias and left-wing groupthink linked to its social justice mission. Critics contend that the construction of “sacred victims” by progressive intellectuals hinders their ability to objectively appraise the circumstances of such vulnerable groups. To address this criticism, we survey 479 sociologists in national universities and colleges in the U.S. regarding three sensitive controversies: urban poverty in the black community; gendered differences in occupational choices; and immigration. We find significant patterns in the data. Commitment to the field’s “moral mission,” preferred research paradigm, gender, and especially political orientation are all significant predictors of sociologists’ views. The results, we suggest, can be understood by conceptualizing the field of sociology as an “emotive community.” In doing so, we draw upon current social psychological research on moral foundations theory developed by Jonathan Haidt and colleagues.
Psychology celebrates diversity, recognizes the value and legitimacy of diverse beliefs, and strives to be inclusive. Yet, the profession lacks sociopolitical diversity. Most psychologists are politically liberal, and conservatives are vastly underrepresented in the profession. Moreover, when sociopolitical views guide the research, advocacy, or professional practice of psychologists, those views most often are liberal. The lack of political diversity in psychology has unintended negative consequences for research, policy advocacy, clinical practice, the design and implementation of social interventions, and professional education. It excludes or marginalizes conservatives and conservative views, having detrimental effects on the profession in each of these areas. This article examines the importance of political diversity and the negative consequences of its absence and provides strategies for increasing sociopolitical pluralism in psychology.
Three experiments supported the hypothesis that people are more willing to express attitudes that could be viewed as prejudiced when their past behavior has established their credentials as nonprejudiced persons. In Study 1, participants given the opportunity to disagree with blatantly sexist statements were later more willing to favor a man for a stereotypically male job. In Study 2, participants who first had the opportunity to select a member of a stereotyped group (a woman or an African American) for a category-neutral job were more likely to reject a member of that group for a job stereotypically suited for majority members. In Study 3, participants who had established credentials as nonprejudiced persons revealed a greater willingness to express a politically incorrect opinion even when the audience was unaware of their credentials. The general conditions under which people feel licensed to act on illicit motives are discussed.
Both liberals and conservatives accuse their political opponents of partisan bias, but is there empirical evidence that one side of the political aisle is indeed more biased than the other? To address this question, we meta-analyzed the results of 51 experimental studies, involving over 18,000 participants, that examined one form of partisan bias—the tendency to evaluate otherwise identical information more favorably when it supports one’s political beliefs or allegiances than when it challenges those beliefs or allegiances. Two hypotheses based on previous literature were tested: an asymmetry hypothesis (predicting greater partisan bias in conservatives than in liberals) and a symmetry hypothesis (predicting equal levels of partisan bias in liberals and conservatives). Mean overall partisan bias was robust (r = .245), and there was strong support for the symmetry hypothesis: Liberals (r = .235) and conservatives (r = .255) showed no difference in mean levels of bias across studies. Moderator analyses reveal this pattern to be consistent across a number of different methodological variations and political topics. Implications of the current findings for the ongoing ideological symmetry debate and the role of partisan bias in scientific discourse and political conflict are discussed.
This study reports results from a new analysis of 17 survey experiment studies that permitted assessment of racial discrimination, drawn from the archives of the Time-sharing Experiments for the Social Sciences. For White participants (n=10 435), pooled results did not detect a net discrimination for or against White targets, but, for Black participants (n=2781), pooled results indicated the presence of a small-to-moderate net discrimination in favor of Black targets; inferences were the same for the subset of studies that had a political candidate target and the subset of studies that had a worker or job applicant target. These results have implications for understanding racial discrimination in the United States, and, given that some of the studies have never been fully reported on in a journal or academic book, the results also suggest the need for preregistration to reduce or eliminate publication bias in racial discrimination studies.
In the 1970s, memory researchers converged on interesting phenomena observed in Korsakoff-syndrome amnesic patients. These patients’ performances on difficult tasks were reliably improved by practice sessions from which they could recall nothing. Related findings of indirect memory effects in college students triggered wide attention to phenomena that, in 1985, were first identified as implicit memory. Within a decade, the indirect measurement methods of implicit memory research had spread to social psychologists’ studies of attitudes and stereotypes. After another two decades, the methods and findings of this developing revolution have revised understanding of how past learning, operating in ways that bypass conscious awareness, nevertheless shapes conscious judgment and perception. This revolution in psychological thinking is on the cusp of reconceiving the relation between unconscious and conscious mental process. Further, it demands researchers’ careful attention to justification for many self-report measures that are now routinely treated as face-valid.
Although past research suggests authoritarianism may be a uniquely right-wing phenomenon, the present two studies tested the hypothesis that authoritarianism exists in both right-wing and left-wing contexts in essentially equal degrees. Across two studies, university (n = 475) and Mechanical Turk (n = 298) participants completed either the RWA (right-wing authoritarianism) scale or a newly developed (and parallel) LWA (left-wing authoritarianism) scale. Participants further completed measurements of ideology and three domain-specific scales: prejudice, dogmatism, and attitude strength. Findings from both studies lend support to an authoritarianism symmetry hypothesis: Significant positive correlations emerged between LWA and measurements of liberalism, prejudice, dogmatism, and attitude strength. These results largely paralleled those correlating RWA with identical conservative-focused measurements, and an overall effect-size measurement showed LWA was similarly related to those constructs (compared to RWA) in both Study 1 and Study 2. Taken together, these studies provide evidence that LWA may be a viable construct in ordinary U.S. samples.
Significance
Public opinion toward some science and technology issues is polarized along religious and political lines. We investigate whether people with more education and greater science knowledge tend to express beliefs that are more (or less) polarized. Using data from the nationally representative General Social Survey, we find that more knowledgeable individuals are more likely to express beliefs consistent with their religious or political identities for issues that have become polarized along those lines (e.g., stem cell research, human evolution), but not for issues that are controversial on other grounds (e.g., genetically modified foods). These patterns suggest that scientific knowledge may facilitate defending positions motivated by nonscientific concerns.
No one factor describes Trump’s supporters. But an array of factors – many of them reflecting five major social psychological phenomena can help to account for this extraordinary political event: authoritarianism, social dominance orientation, prejudice, relative deprivation, and intergroup contact. Research on the topic demonstrates that these theories and concepts of social psychology prove centrally important in helping to understand this unexpected event. This paper describes the supporting data for this statement and demonstrates the close parallels between these American results and those of research on far-right European supporters.
In this chapter, I review key conceptual and methodological sources of bias in psychological measurement, emphasizing those with particular relevance to political phenomena and providing relevant examples of measurement bias in political psychological research. I then review the case of authoritarianism, which until recently was predominantly assessed among political conservatives. This emphasis on right-wing authoritarianism, and paucity of research concerning left-wing authoritarianism, has led to widespread conceptual obstacles to understanding the psychological underpinnings of authoritarianism, illustrating the degree to which measurement bias has key implications for theory development and testing. In closing, I provide several recommendations for reducing political bias in psychological measurement.
This paper explores the connection between bias and academic censorship. After defining terms, we review recent scholarship on varieties of censorship, and varieties of bias. These are then applied to academic processes of peer review, drawing heavily on recent work identifying the ways in which such biases often manifest in academia. We then propose a series of psychological and social processes by which biases can lead to censorship. We conclude the paper with several concrete examples of academic censorship that seem to reflect the processes we have identified.
Epistemic trust among scientists is inevitable. There are two questions about this: (1) What is the content of this trust, what do scientists trust each other for? (2) Is such trust epistemically justified? I argue that if we assume a traditional answer to (1), namely that scientists trust each other to be reliable informants, then the answer to question (2) is negative, certainly for the biomedical and social sciences. This motivates a different construal of trust among scientists and therefore a different answer to (1): scientists trust each other to only testify to claims that are backed by evidence gathered in accordance with prevailing methodological standards. On this answer, trust among scientists is epistemically justified.
The Implicit Association Test (IAT) has been widely discussed as a potential measure of “implicit bias.” Yet the IAT is controversial; research suggests that it is far from clear precisely what the instrument measures, and it does not appear to be a strong predictor of behavior. The presentation of this topic in Introductory Psychology texts is important as, for many students, it is their first introduction to scientific treatment of such issues. In the present study, we examined twenty current Introductory Psychology texts in terms of their coverage of the controversy and presentation of the strengths and weaknesses of the measure. Of the 17 texts that discussed the IAT, a minority presented any of the concerns including the lack of measurement clarity (29%), an automatic preference for White people among African Americans (12%), lack of predictive validity (12%), and lack of caution about the meaning of a score (0%); most provided students with a link to the Project Implicit website (65%). Overall, 82% of the texts were rated as biased or partially biased on their coverage of the IAT. The implications for the perceptions and self-perceptions of students, particularly when a link to Project Implicit is included, are discussed.
This is a study of 12,372 professors in 116 colleges that are the four top US News-ranked colleges in each of 30 states that collect political registration data. We devised the sample to highlight variation in registration arising from individual, college-level, and state-level characteristics. We find an overall Democratic-to-Republican registration ratio of 8.5:1, but age, gender, field, region, and religious affiliation modify the ratios of Democrats to Republicans. This is the first application of logistical modeling to archival faculty registration data. The logistical models mostly confirm the univariate findings but reveal that state- and college-level dummy variables retain their significance when individual, field, and college rank are controlled. Organizational cultures of academic institutions and state political cultures along with better-understood influences of personal and institutional characteristics may influence the propensity of colleges to engage in or deviate from preponderately Democratic hiring.
In this article, we define questionable measurement practices (QMPs) as decisions researchers make that raise doubts about the validity of the measures, and ultimately the validity of study conclusions. Doubts arise for a host of reasons, including a lack of transparency, ignorance, negligence, or misrepresentation of the evidence. We describe the scope of the problem and focus on how transparency is a part of the solution. A lack of measurement transparency makes it impossible to evaluate potential threats to internal, external, statistical-conclusion, and construct validity. We demonstrate that psychology is plagued by a measurement schmeasurement attitude: QMPs are common, hide a stunning source of researcher degrees of freedom, and pose a serious threat to cumulative psychological science, but are largely ignored. We address these challenges by providing a set of questions that researchers and consumers of scientific research can consider to identify and avoid QMPs. Transparent answers to these measurement questions promote rigorous research, allow for thorough evaluations of a study’s inferences, and are necessary for meaningful replication studies.
A poisonous cocktail of othering, aversion, and moralization poses a threat to democracy
The past decade has seen rapid growth in research that evaluates methods for reducing prejudice. This essay reviews 418 experiments reported in 309 manuscripts from 2007 to 2019 to assess which approaches work best and why. Our quantitative assessment uses meta-analysis to estimate average effects. Our qualitative assessment calls attention to landmark studies that are noteworthy for sustained interventions, imaginative measurement, and transparency. However, 76% of all studies evaluate light touch interventions, the long-term impact of which remains unclear. The modal intervention uses mentalizing as a salve for prejudice. Although these studies report optimistic conclusions, we identify troubling indications of publication bias that may exaggerate effects. Furthermore, landmark studies often find limited effects, which suggests the need for further theoretical innovation or synergies with other kinds of psychological or structural interventions. We conclude that much research effort is theoretically and empirically ill-suited to provide actionable, evidence-based recommendations for reducing prejudice.
Expected final online publication date for the Annual Review of Psychology, Volume 72 is January 4, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
This meta-analysis evaluated theoretical predictions from balanced identity theory (BIT) and evaluated the validity of zero points of Implicit Association Test (IAT) and self-report measures used to test these predictions. Twenty-one researchers contributed individual subject data from 36 experiments (total N = 12,773) that used both explicit and implicit measures of the social–cognitive constructs. The meta-analysis confirmed predictions of BIT’s balance–congruity principle and simultaneously validated interpretation of the IAT’s zero point as indicating absence of preference between two attitude objects. Statistical power afforded by the sample size enabled the first confirmations of balance–congruity predictions with self-report measures. Beyond these empirical results, the meta-analysis introduced a within-study statistical test of the balance–congruity principle, finding that it had greater efficiency than the previous best method. The meta-analysis’s full data set has been publicly archived to enable further studies of interrelations among attitudes, stereotypes, and identities.
Members of the field of philosophy have, just as other people, political convictions or, as psychologists call them, ideologies. How are different ideologies distributed and perceived in the field? Using the familiar distinction between the political left and right, we surveyed an international sample of 794 subjects in philosophy. We found that survey participants clearly leaned left (75%), while right-leaning individuals (14%) and moderates (11%) were underrepresented. Moreover, and strikingly, across the political spectrum from very left-leaning individuals and moderates to very right-leaning individuals, participants reported experiencing ideological hostility in the field, occasionally even from those on their own side of the political spectrum. Finally, while about half of the subjects believed that discrimination against left- or right-leaning individuals in the field is not justified, a significant minority displayed an explicit willingness to discriminate against colleagues with the opposite ideology. Our findings are both surprising and important because a commitment to tolerance and equality is widespread in philosophy, and there is reason to think that ideological similarity, hostility, and discrimination undermine reliable belief formation in many areas of the discipline.
In the contemporary context, it is inescapable that racism is a factor in US public opinion. When scholars take stock of the way we typically measure and conceptualize racism, we find reason to reconceptualize the racial resentment scale as a measure of perceptions of the reasons for political inequality. We also see reason to move beyond thinking of racism as an attitude, toward conceptualizing it as a perspective. In addition, we see reason to pay closer attention to the role of elites in creating and perpetuating a role for racism in the way people think about public affairs. The study of racism is evolving in parallel with the broader public discussion: toward a recognition of the complex and fundamental ways it is woven into US culture and political life.
Expected final online publication date for the Annual Review of Political Science, Volume 23 is May 11, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
In 1998, Greenwald, McGhee, and Schwartz proposed that the Implicit Association Test (IAT) measures individual differences in implicit social cognition. This claim requires evidence of construct validity. I review the evidence and show that there is insufficient evidence for this claim. Most important, I show that few studies were able to test discriminant validity of the IAT as a measure of implicit constructs. I examine discriminant validity in several multimethod studies and find little or no evidence of discriminant validity. I also show that validity of the IAT as a measure of attitudes varies across constructs. Validity of the self-esteem IAT is low, but estimates vary across studies. About 20% of the variance in the race IAT reflects racial preferences. The highest validity is obtained for measuring political orientation with the IAT (64%). Most of this valid variance stems from a distinction between individuals with opposing attitudes, whereas reaction times contribute less than 10% of variance in the prediction of explicit attitude measures. In all domains, explicit measures are more valid than the IAT, but the IAT can be used as a measure of sensitive attitudes to reduce measurement error by using a multimethod measurement model.
Prepublication peer review should be abolished. We consider the effects that such a change will have on the social structure of science, paying particular attention to the changed incentive structure and the likely effects on the behaviour of individual scientists. We evaluate these changes from the perspective of epistemic consequentialism. We find that where the effects of abolishing prepublication peer review can be evaluated with a reasonable level of confidence based on presently available evidence, they are either positive or neutral. We conclude that on present evidence abolishing peer review weakly dominates the status quo.
Left Unchecked: Political Hegemony in Political Science and the Flaws It Can Cause - L.J Zigerell
Is climate change real? Does racism still determine who gets ahead? Is sexuality innate? Do immigration and free trade help or hurt the economy? Does gun control reduce violence? Are false convictions common? On these and many other basic questions of fact, Americans are deeply divided. How did this happen? What does it mean? And is there anything we can do about it? Drawing upon several years of original survey data and experiments, Marietta and Barker reach a number of enlightening and provocative conclusions. Among them is that dueling fact perceptions are not so much a result of hyper-partisanship or media propaganda as they are of simple value differences and deepening distrust of authorities. The educated—on both the Left and Right—carry the biggest guns and are the quickest to draw. These duels foster social contempt—even in the workplace—and they warp the electorate. And finally, the remedies that have been proposed don’t seem to holster many weapons; in fact, they add bullets to the chamber in some cases. Marietta and Barker’s pessimistic conclusions will challenge idealistic reformers.
Growing racial, ideological, and cultural polarization within the American electorate contributed to the shocking victory of Donald Trump in the 2016 presidential election. Using data from American National Election Studies surveys, we show that Trump’s unusually explicit appeals to racial and ethnic resentment attracted strong support from white working-class voters while repelling many college-educated whites along with the overwhelming majority of nonwhite voters. However, Trump’s campaign exploited divisions that have been growing within the electorate for decades because of demographic and cultural changes in American society. The 2016 presidential campaign also reinforced another longstanding trend in American electoral politics: the rise of negative partisanship, that is voting based on hostility toward the opposing party and its leaders. We conclude with a discussion of the consequences of deepening partisan and affective polarization for American democracy and the perceptions by both experts and the public of an erosion in its quality. © 2019 by The American Academy of Political and Social Science.
Progress in science relies in part on generating hypotheses with existing observations and testing hypotheses with new observations. This distinction between postdiction and prediction is appreciated conceptually but is not respected in practice. Mistaking generation of postdictions with testing of predictions reduces the credibility of research findings. However, ordinary biases in human reasoning, such as hindsight bias, make it hard to avoid this mistake. An effective solution is to define the research questions and analysis plan before observing the research outcomes-a process called preregistration. Preregistration distinguishes analyses and outcomes that result from predictions from those that result from postdictions. A variety of practical strategies are available to make the best possible use of preregistration in circumstances that fall short of the ideal application, such as when the data are preexisting. Services are now available for preregistration across all disciplines, facilitating a rapid increase in the practice. Widespread adoption of preregistration will increase distinctiveness between hypothesis generation and hypothesis testing and will improve the credibility of research findings.
As public awareness of implicit bias has grown in recent years, studies have raised important new questions about the nature of implicit bias effects. First, implicit biases are widespread and robust on average, yet are unstable across a few weeks. Second, young children display implicit biases indistinguishable from those of adults, which suggests to many that implicit biases are learned early. Yet, if implicit biases are unstable over weeks, how can they be stable for decades? Third, meta-analyses suggest that individual differences in implicit bias are associated weakly, although significantly, with individual differences in behavioral outcomes. Yet, studies of aggregate levels of implicit bias (i.e., countries, states, counties) are strongly associated with aggregate levels of disparities and discrimination. These puzzles are difficult to reconcile with traditional views, which treat implicit bias as an early-learned attitude that drives discrimination among individuals who are high in bias. We propose an alternative view of implicit bias, rooted in concept accessibility. Concept accessibility can, in principle, vary both chronically and situationally. The empirical evidence, however, suggests that most of the systematic variance in implicit bias is situational. Akin to the “wisdom of crowds” effect, implicit bias may emerge as the aggregate effect of individual fluctuations in concept accessibility that are ephemeral and context-dependent. This bias of crowds theory treats implicit bias tests as measures of situations more than persons. We show how the theory can resolve the puzzles posed and generate new insights into how and why implicit bias propagates inequalities.
In my Précis of Social Perception and Social Reality (Jussim 2012, henceforth abbreviated as SPSR ), I argued that the social science scholarship on social perception and interpersonal expectancies was characterized by a tripartite pattern: (1) Errors, biases, and self-fulfilling prophecies in person perception were generally weak, fragile, and fleeting; (2) Social perceptions were often quite accurate; and (3) Conclusions appearing throughout the social psychology scientific literature routinely overstated the power and pervasiveness of expectancy effects, and ignored evidence of accuracy. Most commentators concurred with the validity of these conclusions. Two, however, strongly disagreed with the conclusion that the evidence consistently has shown that stereotypes are moderately to highly accurate. Several others, while agreeing with most of the specifics, also suggested that those arguments did not necessarily apply to contexts outside of those covered in SPSR. In this response, I consider all these aspects: the limitations to the tripartite pattern, the role of politics and confirmation biases in distorting scientific conclusions, common obstructions to effective scientific self-correction, and how to limit them.