Arguments discrediting the value-free ideal of science have left us with the question of how to distinguish desirable values from biases that compromise the reliability of research. In this paper, I argue for a characterization of cognitive biases as deviations of thought processes that systematically lead scientists to the wrong conclusions. In particular, cognitive biases could help us understand a crucial issue in science today: how systematic error is introduced in research outcomes, even when research (...) is evaluated as of good quality. To conclude, I suggest that some debiasing mechanisms have great potential for countering implicit methodological biases in science. (shrink)

Reporting biases refer to a truncated pool of published studies with the resulting suppression or omission of some empirical findings. Such biases can occur in positive research paradigms that try to uncover correlations and causal relationships in the social world by using the empirical methods of science. Furthermore, reporting biases can come about because of authors who do not write papers that report unfavorable results despite strong efforts made to find previously accepted evidence and because of (...) a higher rejection rate of studies documenting contradictory evidence. Reporting biases are a serious concern because the conclusions of systematic reviews and meta-analyses can be misleading. The authors show that published evidence in win-win corporate social responsibility research tends to overestimate efficiency. The research field expects to find a positive association between corporate social performance and corporate financial performance, and findings meet that expectation. The authors explain how this pattern may reflect reporting bias. The empirical results show strong tentative evidence for a positive reporting bias in the CSP–CFP literature but only weak tentative evidence for CSP efficiency. The study also examines which factors, such as time trends, publication outlet, and study characteristics, are associated with higher reporting biases within this literature. (shrink)

Cognitive biases that affect decision making may affect the decisions of citizens that influence public policy. To the extent that decisions follow principles other than maximizing utility for all, it is less likely that utility will be maximized, and the citizens will ultimately suffer the results. Here I outline some basic arguments concerning decisions by citizens, using voting as an example. I describe two types of values that may lead to sub-optimal consequences when these values influence political behavior: moralistic (...) values (which people are willing to impose on others regardless of the consequences) and protected values (PVs, values protected from trade-offs). I present evidence against the idea that voting is expressive, i.e., that voters aim to express their moral views rather than to have an effect on outcomes. I show experimentally that PVs are often moralistic. Finally, I present some data that citizens’ think of their duty in a parochial way, neglecting out-groups. I conclude that moral judgments are important determinants of citizen behavior, that these judgments are subject to biases and based on moralistic values, and that, therefore, outcomes are probably less good than they could be. (shrink)

Topics in Cognitive Science, Volume 14, Issue 3, Page 508-527, July 2022.

In a study of the kin investment of aunts and uncles we show that the laterality effect expected as a result of paternity uncertainty is statistically reliable but somewhat smaller than the sex effect. Matrilateral aunts invest significantly more than patrilateral aunts, and the same is true for uncles. Regardless of laterality, however, aunts invest significantly more than uncles. Multivariate controls show that the matrilateral bias is fully independent of any age or distance confounds that might result from sex differences (...) in age at marriage or dispersal. We discuss our results in relation to recent findings on the kin investment of grandparents (Euler and Weitzel 1996). In addition, we propose a simple method for estimating the level of paternity uncertainty from kin investment data; application of this method to our data on aunts and uncles suggests that between 13% and 20% of children are not the offspring of their putative father. Our parallel analyses of Euler and Weitzel’s (1996) data on grandparental investment suggest a similar estimate, that paternity uncertainty lies between 9% and 17%. (shrink)

Financial and prosocial biases in favor of attractive adults have been documented in the labor market, in social transactions in everyday life, and in studies involving experimental economic games. According to the taste-based discrimination model developed by economists, attractiveness-related financial and prosocial biases are the result of preferences or prejudices similar to those displayed toward members of a particular sex, racial, ethnic, or religious group. Other explanations proposed by economists and social psychologists maintain that attractiveness is a marker (...) of personality, intelligence, trustworthiness, professional competence, or productivity. Evolutionary psychologists have argued that attractive adults are favored because they are preferred sexual partners. Evidence that stereotypes about attractive people are causally related to financial or prosocial biases toward them is weak or nonexistent. Consistent with evolutionary explanations, biases in favor of attractive women appear to be more consistent or stronger than those in favor of attractive men, and biases are more consistently reported in interactions between opposite-sex than same-sex individuals. Evolutionary explanations also account for increased prosocial behavior in situations in which attractive individuals are simply bystanders. Finally, evolutionary explanations are consistent with the psychological, physiological, and behavioral changes that occur when individuals are exposed to potential mates, which facilitate the expression of courtship behavior and increase the probability of occurrence of mating. Therefore, multiple lines of evidence suggest that mating motives play a more important role in driving financial and prosocial biases toward attractive adults than previously recognized. (shrink)

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on (...) shared and non-shared features. Feature distinctiveness predicted order of acquisition across all measures: Words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non-shared features and did not include shared features. This indicates that shared features may play less of a role in early word learning than non-shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects' distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning. (shrink)

Most philosophers accept some version of the requirement of total evidence (RTE), which tells us to always update on our complete evidence, which often includes ‘background information’ about how that evidence was collected. But different philosophers disagree about how to implement that requirement. In this article, I argue against one natural picture of how to implement the RTE in likelihood arguments, and I argue in favor of a different picture. I also apply my picture to the controversy over the so-called (...) ‘Objection from Anthropic Bias’ to the fine-tuning argument, and argue that the Objection from Anthropic Bias fails. (shrink)

Scientific Testimony concerns the roles of scientific testimony in science and society. The book develops a positive alternative to a tradition famously expressed by the slogan of the Royal Society Nullius in verba ("Take nobody's word for it"). This book argues that intra-scientific testimony—i.e., testimony between collaborating scientists—is not in conflict with the spirit of science or an add-on to scientific practice. On the contrary, intra-scientific testimony is a vital part of science. This is illustrated by articulating (...) epistemic norms of intra-scientific testimony and arguing that they are vital to scientific methodology on a par with other scientific norms governing scientific observation and data analysis. -/- The book also provides an account of public scientific testimony—i.e., scientific testimony to the lay population. This is done by integrating philosophical resources with empirical research on the science of science communication. For example, various misconceptions about science and folk epistemological biases are diagnosed as factors that contribute to science skepticism. This diagnosis provides the basis for developing novel norms for science communication that are sensitive to the psychological and social obstacles to laypersons' uptake of it. Finally, the volume discusses how public scientific testimony is best embedded in society and argues that it is critical for societies that pursue the ideals of deliberative democracy. Scientific Testimony draws on philosophy of science, social epistemology, and empirical research to provide a wide-ranging account of the roles of scientific testimony within scientific practice and within the wider society. (shrink)

One of the innovative approaches in contemporary philosophical ontology consists in the assumption of a plurality of ontologies based on different metaphysical presuppositions. Such presuppositions involve, among others, the identification of relevant properties for the objects of our domain as a guiding principle in uncovering what it is to be considered intrinsic and what could be the mere effect of selection preferences based on objective or subjective criteria. A remarkable example of the application of a background metaphysical theory in astrophysics (...) is the problem of selection biases in detecting cosmological objects, such as supernovae, galaxies and gamma-ray bursts. We will show that it is valuable to be aware of the importance of uncovering this type of background theory to better understand selection effects and to promote a novel approach in scientific research. (shrink)

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on (...) shared and non‐shared features. Feature distinctiveness predicted order of acquisition across all measures: Words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non‐shared features (object dissimilarity) and did not include shared features (object similarity). This indicates that shared features may play less of a role in early word learning than non‐shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects' distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning. (shrink)

Gatekeeping, or determining membership of your group, is crucial to science: the moniker ‘scientific’ is a stamp of epistemic quality or even authority. But gatekeeping in science is fraught with dangers. Gatekeepers must exclude bad science, science fraud and pseudoscience, while including the disagreeing viewpoints on which science thrives. This is a difficult tightrope, not least because gatekeeping is a human matter and can be influenced by biases such as groupthink. After spelling out these (...) general tensions around gatekeeping in science, we shed light on them with a case study from psychology. This concerns whether academic psychologists rightly or wrongly classify the applied-psychology framework of NLP (‘neuro-linguistic programming’) as unscientific and even pseudoscientific. This example of gatekeeping is particularly instructive because both the NLP community and the psychology community, we argue, make legitimate but also illegitimate moves. This case gives rise to several general insights about gatekeeping in science more generally. (shrink)

The English language now dominates scientific communications. Yet, many scientists have English as their second language. Their English proficiency may therefore often be more limited than that of a ‘native speaker’, and their scientific contributions (e.g. manuscripts) in English may frequently contain linguistic features that disrupt the fluency of a reader’s, or listener’s information processing even when the contributions are understandable. Scientific gatekeepers (e.g. journal reviewers) sometimes cite these features to justify negative decisions on manuscripts. Such justifications may rest on (...) the prima facie plausible assumption that linguistic characteristics that hinder fast and easy understandability of scientific contributions are epistemically undesirable in science. I shall raise some doubts about this assumption by drawing on empirical research on processing fluency and its biasing effects. I also argue that directing scientists with English as a foreign language toward approaching ‘native-level’ English can have the negative consequence of reducing their potential to make scientific belief formation more reliable. These points suggest that one seemingly compelling justification for linguistically discriminating against scientific contributions in ‘non-native’ English is questionable and that the common insistence by scientific gatekeepers on ‘native-like’ English may be epistemically harmful to science. (shrink)

In this article, we develop a hierarchical Bayesian model of learning in a general type of artificial language‐learning experiment in which learners are exposed to a mixture of grammars representing the variation present in real learners’ input, particularly at times of language change. The modeling goal is to formalize and quantify hypothesized learning biases. The test case is an experiment (Culbertson, Smolensky, & Legendre, 2012) targeting the learning of word‐order patterns in the nominal domain. The model identifies internal (...) class='Hi'>biases of the experimental participants, providing evidence that learners impose (possibly arbitrary) properties on the grammars they learn, potentially resulting in the cross‐linguistic regularities known as typological universals. Learners exposed to mixtures of artificial grammars tended to shift those mixtures in certain ways rather than others; the model reveals how learners’ inferences are systematically affected by specific prior biases. These biases are in line with a typological generalization—Greenberg's Universal 18—which bans a particular word‐order pattern relating nouns, adjectives, and numerals. (shrink)

Approaching science by considering the epistemological virtues which scientists see as constitutive of good science, and the way these virtues trade-off against one another, makes it possible to capture action that may be lost by approaches which focus on either the theoretical or institutional level. Following Wimsatt (1984) I use the notion of heuristics and biases to help explore a case study from the history of biology. Early in the 20th century, mutation theorists and natural historians fought (...) over the role that isolation plays in evolution. This debate was principally about whether replication was the central scientific virtue (and hence the ultimate goal of science to replace non-experimental evidence with experimental evidence) or whether consilience of inductions was the central virtue (and hence, as many kinds of evidence as possible should be pursued). (shrink)

Metaphysical considerations aside, today’s inheritors of the tradition of natural philosophy are primarily scientists. However, they are oblivious to the human factor involved in science and in seeing how political, religious, and other ideologies contaminate our visions of nature. In general, philosophers observe human (historical, sociological, and psychological) processes within the construction of theories, as well as in the development of scientific activity itself. -/- In our time, feminism—along with accompanying ideas of identity politics under the slogan “diversity, inclusion, (...) equity”—has emerged in science policies. The vast majority of scientists (including myself) are convinced that discrimination is reprehensible. We also believe that all individuals of any sex, race, ethnic group, or ideology should be valued in academia solely based on his or her merits and potential through equality programs. However, as I will show in this article, political indoctrination has inadmissibly undertaken the struggle for equality in academic institutions in Western countries. I argue here that universities and research institutes should be politically free (neutral) to encourage academic freedom. -/- One negative aspect of equality programs is that worldwide, scientists are harassed for expressing opinions related to the “gender” issue. This situation severely restricts scientists’ freedom of expression, even within the limits of the law. Codes of conduct extending beyond legal boundaries are examples of this issue. Scientists who express their views about “gender” are often harassed, bullied, and socially or academically excluded. Thus, we are witnessing a wave of proselytizing in research institutes and science-associated media. Today, there is widespread biased propaganda of “victimhood”. This propaganda proposes positive discrimination and increasing women’s participation in unnatural ways. It also bends the history of science by overvaluing the creations of forgotten women, offering lectures on indoctrination, organizing congresses on gender and science, and persecuting anyone who sees the subject differently. All of this covered by a multitude of associations that financially benefit from these discourses through succulent subsidies of public money. Apparently, feminism is no longer about fighting against discrimination. Instead, it is about imposing an ideology and giving more power to one group of people. Thus, we must ask whether the end justifies the means. (shrink)

Prior work has demonstrated that young children in the US and the Ecuadorian Amazon preferentially remember information about the dangerousness of an animal over both its name and its diet. Here we explore if this bias is present among older children and adults in Fiji through the use of an experimental learning task. We find that a content bias favoring the preferential retention of danger and toxicity information continues to operate in older children, but that the magnitude of the bias (...) diminishes with age and is absent in adults. We also find evidence that fitness costs likely impact the types of mistakes that participants make in their attributions of dangerousness and poisonousness. These results suggest that natural selection has shaped the way in which we learn and make inferences about unfamiliar animal species over ontogeny, and that future research is needed on how content biases may vary across the life course. (shrink)

Women working in the sciences face obstacles at virtually every step along their career paths. From subtle slights to blatant biases, deep systemic problems block women from advancing or push them out of science and technology entirely. Women in Science Now examines solutions to this persistent gender gap, offering new perspectives on how to make science more equitable and inclusive for all. This book shares stories and insights of women from a range of backgrounds working in (...) various disciplines, illustrating the journeys that brought them to the sciences, the challenges they faced along the way, and the important contributions they have made to their fields. Lisa M. P. Munoz combines these narratives with a wealth of data to illuminate the size and scope of the challenges women scientists face, while highlighting research-based solutions to help overcome these obstacles. She presents groundbreaking studies in social psychology and organizational behavior that are informing novel approaches for combating historic and ongoing inequities. Through a combined focus on personal experiences and social-science research, this timely book provides both a path toward greater gender equity and an inspiring vision of science and scientists. (shrink)

Current perspectives on attractiveness-related prosocial biases emphasize the contribution of evolutionarily shaped mating drives. Here, we extend these concepts by highlighting the pivotal role of the hypothalamic peptide oxytocin in augmenting the salience and rewarding value of social stimuli, including the partner's face, thereby fostering social bonding in general and the stability of monogamous pair bonds and offspring care in particular.

Algorithmic biases, or algorithmic unfairness, have been a topic of public and scientific scrutiny for the past years, as increasing evidence suggests the pervasive assimilation of human cognitive biases and stereotypes in such systems. This research is specifically concerned with analyzing the presence of discursive biases in the text generated by GPT-3, an NLPM which has been praised in recent years for resembling human language so closely that it is becoming difficult to differentiate between the human and (...) the algorithm. The pertinence of this research object is substantiated by the identification of race, gender and religious biases in the model’s completions in recent research, suggesting that the model is indeed heavily influenced by human cognitive biases. To this end, this research inquires: How does the Natural Language Processing Model GPT-3 replicate existing social biases?. This question is addressed through the scrutiny of GPT-3’s completions using Critical Discourse Analysis (CDA), a method which has been deemed as amply valuable for this research as it is aimed at uncovering power asymmetries in language. As such, the analysis is specifically centered around the analysis of gender and race biases in the model’s generated text. Research findings suggest that GPT-3’s language generation model significantly exacerbates existing social biases while replicating dangerous ideologies akin to white supremacy and hegemonic masculinity as factual knowledge. (shrink)

Many natural and biological phenomena can be depicted as networks. Theoretical and empirical analyses of networks have become prevalent. I discuss theoretical biases involved in the delineation of biological networks. The network perspective is shown to dissolve the distinction between regulatory architecture and regulatory state, consistent with the theoretical impossibility of distinguishing a priori between “program” and “data”. The evolutionary significance of the dynamics of trans-generational and inter-organism regulatory networks is explored and implications are presented for understanding the evolution (...) of the biological categories development-heredity; plasticity-evolvability; and epigenetic-genetic. (shrink)

In typical development, word learning goes from slow and laborious to fast and seemingly effortless. Typically developing 2-year-olds seem to intuit the whole range of things in a category from hearing a single instance named—they have word-learning biases. This is not the case for children with relatively small vocabularies. We present a computational model that accounts for the emergence of word-learning biases in children at both ends of the vocabulary spectrum based solely on vocabulary structure. The results of (...) Experiment 1 show that late-talkers' and early-talkers' noun vocabularies have different structures and that neural networks trained on the vocabularies of individual late talkers acquire different word-learning biases than those trained on early-talker vocabularies. These models make novel predictions about the word-learning biases in these two populations. Experiment 2 tests these predictions on late- and early-talking toddlers in a novel noun generalization task. (shrink)

_Anthropic Bias_ explores how to reason when you suspect that your evidence is biased by "observation selection effects"--that is, evidence that has been filtered by the precondition that there be some suitably positioned observer to "have" the evidence. This conundrum--sometimes alluded to as "the anthropic principle," "self-locating belief," or "indexical information"--turns out to be a surprisingly perplexing and intellectually stimulating challenge, one abounding with important implications for many areas in science and philosophy. There are the philosophical thought experiments and (...) paradoxes: the Doomsday Argument; Sleeping Beauty; the Presumptuous Philosopher; Adam & Eve; the Absent-Minded Driver; the Shooting Room. And there are the applications in contemporary science: cosmology ; evolutionary theory ; the problem of time's arrow ; quantum physics ; game-theory problems with imperfect recall ; even traffic analysis. _Anthropic Bias_ argues that the same principles are at work across all these domains. And it offers a synthesis: a mathematically explicit theory of observation selection effects that attempts to meet scientific needs while steering clear of philosophical paradox. (shrink)

This article examines the concept of wishful thinking in philosophical literature on science and values. It suggests that this term tends to be used in an overly broad manner that fails to distinguish between separate types of bias, mechanisms that generate biases, and general theories that might explain those mechanisms. I explain how confirmation bias is distinct from wishful thinking and why it is more useful for examining the relationship between cognitive bias and beliefs about the existence of (...) injustices. (shrink)

Inferences from clinical research results to estimates of therapeutic effectiveness suffer due to various biases. I argue that predictions of medical effectiveness are prone to failure because current medical research overlooks the impacts of a particularly detrimental set of biases: meta-biases. Meta-biases are linked to higher-level characteristics of medical research and their effects are only observed when comparing sets of studies that share certain meta-level properties. I offer a model for correcting research results based on meta-research (...) evidence, the bias dynamics model, which employs regularly updated empirical bias coefficients to attenuate estimates of therapeutic effectiveness. (shrink)

Biases in cognition are ubiquitous. Social psychologists suggested biases and stereotypes serve a multifarious set of cognitive goals, while at the same time stressing their potential harmfulness. Recently, biases and stereotypes became the purview of heated debates in the machine learning community too. Researchers and developers are becoming increasingly aware of the fact that some biases, like gender and race biases, are entrenched in the algorithms some AI applications rely upon. Here, taking into account several (...) existing approaches that address the problem of implicit biases and stereotypes, we propose that a strategy to cope with this phenomenon is to unmask those found in AI systems by understanding their cognitive dimension, rather than simply trying to correct algorithms. To this extent, we present a discussion bridging together findings from cognitive science and insights from machine learning that can be integrated in a state-of-the-art semantic network. Remarkably, this resource can be of assistance to scholars (e.g., cognitive and computer scientists) while at the same time contributing to refine AI regulations affecting social life. We show how only through a thorough understanding of the cognitive processes leading to biases, and through an interdisciplinary effort, we can make the best of AI technology. (shrink)

Journal peer review is an essential part of academic practices.1 But how well does it serve its purpose and which factors have an influence on how close it comes to achieving its aims? Peer review has been widely discussed in empirical literature: it has been studied both qualitatively and quantitatively (e.g., by Cole, who in his 1992 book uses data on how grant applications submitted to National Science Foundation were...

The notion of mutation is applicable to the generation of novel designs and solutions in engineering and science. This suggests that engineers and scientists have to work against the biases identified in counterfactual thinking. Therefore, imagination appears a lot less rational than claimed in the target article.

The cognitive science of religion is an emerging field of cognitive science that gathers insights from different disciplines to explain how humans acquire and transmit religious beliefs. For the CSR scholars, the human mental tools have specific biases that make them susceptible to acceptance and transmission of religious beliefs. This article examines the characteristics of these biases and how they work, and shows that although our innate cognitive tendencies make our minds generally receptive to religion, they (...) do not explain the emergence and endurance of specific religious beliefs in a particular culture. We will also show that although advocates of CSR study religion as a 'natural' phenomenon, and seek to discover the natural causes of the formation, acceptance, transmission and prevalence of religious beliefs, their efforts do not lead to decrease the validity of religious beliefs and rejection of 'non-natural' explanations of religious beliefs. (shrink)

_Anthropic Bias_ explores how to reason when you suspect that your evidence is biased by "observation selection effects"--that is, evidence that has been filtered by the precondition that there be some suitably positioned observer to "have" the evidence. This conundrum--sometimes alluded to as "the anthropic principle," "self-locating belief," or "indexical information"--turns out to be a surprisingly perplexing and intellectually stimulating challenge, one abounding with important implications for many areas in science and philosophy. There are the philosophical thought experiments and (...) paradoxes: the Doomsday Argument; Sleeping Beauty; the Presumptuous Philosopher; Adam & Eve; the Absent-Minded Driver; the Shooting Room. And there are the applications in contemporary science: cosmology ; evolutionary theory ; the problem of time's arrow ; quantum physics ; game-theory problems with imperfect recall ; even traffic analysis. _Anthropic Bias_ argues that the same principles are at work across all these domains. And it offers a synthesis: a mathematically explicit theory of observation selection effects that attempts to meet scientific needs while steering clear of philosophical paradox. (shrink)

Informal communication and interaction are integral components of the practice of science, including the doctoral process. This article argues that women are disadvantaged in the informal milieu of the higher education in science, and that this milieu is not uniform everywhere. It posits that to understand the position of women in science in South Asian countries like India, the inquiry has to be conceptualized in the specific social, historical, and institutional context. Through a questionnaire survey comparing male (...) and female perceptions, and qualitative interviews with women, an attempt has been made to understand the nature of Indian women's problems in the informal doctoral science environment. The findings indicate that though the nature of problems appears to be similar to those faced by the women in science in the West, the specific form of biases varies, and that the cultural context molds the specific forms of discrimination. This has implications for future research and policies. (shrink)

This volume presents the first systematic evaluation of a feminist epistemology of sciences' power to transform both the practice of science and our society. Unlike existing critiques, this book questions the fundamental feminist suggestion that purging science of alleged male biases will advance the cause of both science and by extension, social justice. The book is divided into four sections: the strange status of feminist epistemology, testing feminist claims about scientific practice, philosophical and political critiques of (...) feminist epistemology, and future prospects of feminist epistemology. Each of the essays3/4most of which are original to this text3/4 directly confronts the very idea that there could be a feminist epistemology or philosophy of science. Rather than attempting to deal in detail with all of the philosophical views that fall under the general rubric of feminist epistemology, the contributors focus on positions that provide the most influential perspectives on science. Not all of the authors agree amongst themselves, of course, but each submits feminist theories to careful scrutiny. Scrutinizing Feminist Epistemology provides a timely, well-rounded, and much needed examination of the role of gender in scientific research. (shrink)

Interest in science and math plays an important role in encouraging STEM motivation and career aspirations. This interest decreases for girls between late childhood and adolescence. Relatedly, positive mentoring experiences with female teachers can protect girls against losing interest. The present study examines whether visitors to informal science learning sites differ in their expressed science and math interest, as well as their science and math stereotypes following an interaction with either a male or female educator. Participants (...) were visitors to one of four ISLS in the United States and United Kingdom. Following an interaction with a male or female educator, they reported their math and science interest and responded to math and science gender stereotype measures. Female participants reported greater interest in math following an interaction with a female educator, compared to when they interacted with a male educator. In turn, female participants who interacted with a female educator were less likely to report male-biased math gender stereotypes. Self-reported science interest did not differ as a function of educator gender. Together these findings suggest that, when aiming to encourage STEM interest and challenge gender stereotypes in informal settings, we must consider the importance of the gender of educators and learners. (shrink)

Constraints on the types of speech errors observed can be accounted for by a frame/content distinction, but connectionist modeling shows that they do not require this distinction. The constraints may arise instead from the statistical properties of our language, in particular, the sequential biases observed in the vocabulary. Nevertheless, there might still be a role for the frame/content distinction in syntactic planning.

Philip Kitcher rejects the global pessimists' view that the conclusions reached in inquiry are determined by the interests of some segment of the population, arguing that only some inquiries, for example, inquiries into race and gender, are adversely affected by interests. I argue that the biases Kitcher believes affect such inquiries are operative in all domains, but the prevalence of such biases does not support global pessimism. I argue further that in order to address the global pessimists' concerns, (...) the scientific community needs criticism from people with diverse interests and background assumptions. (shrink)

English abstract: Feminist philosophers of science have argued that various biases can and do influence the results of scientific investigations. Two kinds of arguments have been most influential: On the one hand, it has been argued that biased assumptions frequently bridge the gap between observation and theory associated with ‘the underdetermination thesis’. On the other hand, it has been argued that biased value judgments determine when the evidence in favor of a particular theory is considered sufficiently strong for (...) the theory to be accepted as true. This paper argues that bias can influence the results of scientific investigations via a third route. Briefly, biases can and do influence which theories are seriously proposed and considered in scientific communities, which in turn leads to otherwise promising theories being ignored when scientists are choosing between such theories. In the final section, I suggest that this result speaks in favor of taking a quite radical approach to eliminating unwanted biases in science. (shrink)

Research suggests that interventions involving extensive training or counterconditioning can reduce implicit prejudice and stereotyping, and even susceptibility to stereotype threat. This research is widely cited as providing an “existence proof” that certain entrenched social attitudes are capable of change, but is summarily dismissed—by philosophers, psychologists, and activists alike—as lacking direct, practical import for the broader struggle against prejudice, discrimination, and inequality. Criticisms of these “debiasing” procedures fall into three categories: concerns about empirical efficacy, about practical feasibility, and about the (...) failure to appreciate the underlying structural-institutional nature of discrimination. I reply to these criticisms of debiasing, and argue that a comprehensive strategy for combating prejudice and discrimination should include a central role for training our biases away. (shrink)

This paper examines the emergence of a new approach to stratigraphic complexity, first in geology and then, following its creative appropriation, in paleobiology. The approach was associated with a set of models that together transformed stratigraphic geology in the decades following 1970. These included the influential models of depositional sequences developed by Peter Vail and others at Exxon. Transposed into paleobiology, they gave researchers new resources for studying the incompleteness of the fossil record and for removing biases imposed by (...) the processes of sedimentary accumulation. In addition, they helped reconfigure the cultural landscape of paleobiology, consolidating a growing emphasis on fieldwork and eroding the barrier that had been erected in the 1970s between “paleontology” and “paleobiology.” This paper traces these developments, paying special attention to the simulation models of stratigraphic paleobiologist Steven Holland. It also considers how the integration of sequence and event stratigraphy and paleobiology has begun to influence long-running discussions of incompleteness and bias in the fossil record. (shrink)

Philip Kitcher rejects the global pessimists' view that the conclusions reached in inquiry are determined by the interests of some segment of the population, arguing that only some inquiries, for example, inquiries into race and gender, are adversely affected by interests. I argue that the biases Kitcher believes affect such inquiries are operative in all domains, but the prevalence of such biases does not support global pessimism. I argue further that in order to address the global pessimists' concerns, (...) the scientific community needs criticism from people with diverse interests and background assumptions. (shrink)

This review begins with a detailed focus on the Turnaway Study, which addresses associations among early abortion, later abortion, and denied abortion relative to various outcomes including mental health indicators. The Turnaway Study was comprised of 516 women; however, an exact percentage of the population is not discernable due to missing information. Extrapolating from what is known reveals a likely low of 0.32% to a maximum of 3.18% of participants sampled from the available the pool. Motivation for conducting the Turnaway (...) Study, methodological deficiencies (sampling issues and others), and bias are specifically addressed. Despite serious departures from accepted scientific practices, journals in psychology and medicine have published dozens of articles generated from the study’s data. The high volume of one-sided publications has stifled dialogue on potential adverse psychological consequences of this common procedure. Following a critical analysis of the Turnaway Study, an overview of the strongest studies on abortion and mental health is offered. This comprehensive literature comprised of numerous large-scale studies from across the globe has been largely overlooked by scientists and the public, while the Turnaway Study dominates the media, information provided to women, and legal challenges involving abortion restrictions. In the final section of this article, literature reviews by professional organizations are considered, demonstrating that the biased science characterizing the Turnaway Study is aligned with a pervasive and systemic phenomenon wherein deriving reliable and valid results via careful attention to methodology and scrutiny by the scientific community have been supplanted by politics. (shrink)

How does a complex organism develop from a relatively simple, homogeneous mass? The usual answer is: through the (context‐dependent) execution of species‐specific genetic instructions specifying the development of that organism. Commentators are sometimes skeptical of this usual answer, but of course not all commentators, and not always for the same reasons. Here I attempt to lay bare the logical structure of the usual answer through an extended analysis of the heuristics and methodological principles at play in the exploration and explanation (...) of development—and also to show a critical ambiguity that renders the usual answer suspect. (shrink)

The study of ethical behavior and ethical decision making is of increasing importance in many fields, and there is a growing literature addressing the issue. However, research examining differences in ethical decision making across fields and levels of experience is limited. In the present study, biases that undermine ethical decision making and compensatory strategies that may aid ethical decision making were identified in a series of interviews with 63 faculty members across six academic fields and three levels of rank (...) as well as across gender. The degree to which certain biases and compensatory strategies were used in justifications for responses to ethical situations was compared across fields, level of experience, and gender. Major differences were found across fields for several biases and compensatory strategies, including biases and compensatory strategies related to use of professional field principles and field-specific guidelines. Furthermore, full professors tend to differ greatly from assistant and associate professors on a number of constructs, and there were differences in the consistency with which biases and compensatory strategies were displayed within these various groups. Implications of these findings for ethics training and future research are discussed. (shrink)