Results for 'Evaluation bias'

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  1.  20
    Implicit evaluation bias induced by approach and avoidance.M. L. Woud, E. S. Becker & M. Rinck - 2011 - Cognition and Emotion 25 (7):1309-1310.
  2.  12
    How the evaluability bias shapes transformative decisions.Yoonseo Zoh, L. A. Paul & M. J. Crockett - 2024 - Synthese 203 (2):1-22.
    Our paper contributes to the rapidly expanding body of experimental research on transformative decision making, and in the process, marks out a novel empirical interpretation for assessments of subjective value in transformative contexts. We start with a discussion of the role of subjective value in transformative decisions, and then critique extant experimental work that explores this role, with special attention to Reuter and Messerli (2018). We argue that current empirical treatments miss a crucial feature of practical deliberation manifesting across a (...)
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  3.  22
    Implicit evaluation bias induced by approach and avoidance.Marcella L. Woud, Eni S. Becker & Mike Rinck - 2008 - Cognition and Emotion 22 (6):1187-1197.
  4. The epistemic impact of theorizing: generation bias implies evaluation bias.Finnur Dellsén - 2020 - Philosophical Studies 177 (12):3661-3678.
    It is often argued that while biases routinely influence the generation of scientific theories, a subsequent rational evaluation of such theories will ensure that biases do not affect which theories are ultimately accepted. Against this line of thought, this paper shows that the existence of certain kinds of biases at the generation-stage implies the existence of biases at the evaluation-stage. The key argumentative move is to recognize that a scientist who comes up with a new theory about some (...)
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  5.  20
    The mediating role of state maladaptive emotion regulation in the relation between social anxiety symptoms and self-evaluation bias.Laurel D. Sarfan, Meghan W. Cody & Elise M. Clerkin - 2018 - Cognition and Emotion 33 (2):361-369.
    ABSTRACTAlthough social anxiety symptoms are robustly linked to biased self-evaluations across time, the mechanisms of this relation remain unclear. The present study tested three maladaptive emotion regulation strategies – state post-event processing, state experiential avoidance, and state expressive suppression – as potential mediators of this relation. Undergraduate participants rated their social skill in an impromptu conversation task and then returned to the laboratory approximately two days later to evaluate their social skill in the conversation again. Consistent with expectations, state post-event (...)
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  6. Evaluating Student Evaluations of Teaching: a Review of Measurement and Equity Bias in SETs and Recommendations for Ethical Reform.Rebecca J. Kreitzer & Jennie Sweet-Cushman - 2021 - Journal of Academic Ethics 20 (1):73-84.
    Student evaluations of teaching are ubiquitous in the academe as a metric for assessing teaching and frequently used in critical personnel decisions. Yet, there is ample evidence documenting both measurement and equity bias in these assessments. Student Evaluations of Teaching have low or no correlation with learning. Furthermore, scholars using different data and different methodologies routinely find that women faculty, faculty of color, and other marginalized groups are subject to a disadvantage in SETs. Extant research on bias on (...)
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  7.  30
    Evaluating solutions to sponsorship bias.M. Doucet & S. Sismondo - 2008 - Journal of Medical Ethics 34 (8):627-630.
    More than 40 primary studies, and three recent systematic reviews and meta-analyses, have shown a clear association between pharmaceutical industry funding of clinical trials and pro-industry results. Industry sponsorship biases published scientific research in favour of the sponsors, a result of the strong interest commercial sponsors have in obtaining favourable results.Three proposed remedies to this problem are widely agreed upon among those concerned with the level of sponsorship bias: financial disclosure, reporting standards and trial registries. This paper argues that (...)
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  8.  49
    Response Bias Correction in the Process Dissociation Procedure: Approaches, Assumptions, and Evaluation.Eyal Reingold - 1995 - Consciousness and Cognition 5 (1-2):232-254.
    Buchner, Erdfelder, and Vaterrodt-Plunnecke (1995) advocated an exposition of the process dissociation procedure within the framework of multinomial modeling. Among the misleading aspects of this exposition is its tendency to obscure the overlap between processes. In contrast, clarifying these crucial interactions leads to a general classification of response bias corrections to the process dissociation procedure. This scheme, in which corrective models are classified on the basis of process interactions, clarifies the assumptions underlying previously proposed corrections. As an illustration of (...)
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  9.  32
    Manuscript evaluation by journal referees and editors: Randomness or bias?Andrew M. Colman - 1982 - Behavioral and Brain Sciences 5 (2):205-206.
  10. Why future-bias isn't rationally evaluable.Callie K. Phillips - 2021 - Res Philosophica 98 (4):573-596.
    Future-bias is preferring some lesser future good to a greater past good because it is in the future, or preferring some greater past pain to some lesser future pain because it is in the past. Most of us think that this bias is rational. I argue that no agents have future-biased preferences that are rationally evaluable—that is, evaluable as rational or irrational. Given certain plausible assumptions about rational evaluability, either we must find a new conception of future-bias (...)
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  11.  60
    Evaluation of a 'bias-free' measure of awareness.Simon Evans & Paul Azzopardi - 2007 - Spatial Vision. Special Issue 20 (1-2):61-77.
  12. The Myside Bias in Argument Evaluation: A Bayesian Model.Edoardo Baccini & Stephan Hartmann - 2022 - Proceedings of the Annual Meeting of the Cognitive Science Society 44:1512-1518.
    The "myside bias'' in evaluating arguments is an empirically well-confirmed phenomenon that consists of overweighting arguments that endorse one's beliefs or attack alternative beliefs while underweighting arguments that attack one's beliefs or defend alternative beliefs. This paper makes two contributions: First, it proposes a probabilistic model that adequately captures three salient features of myside bias in argument evaluation. Second, it provides a Bayesian justification of this model, thus showing that myside bias has a rational Bayesian explanation (...)
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  13.  3
    Evaluation of a Smartphone Application on the Reduction of Attentional Bias Toward Alcohol Among Students†.Valentin Flaudias, Oulmann Zerhouni, Nadia Chakroun-Baggioni, Ingrid De Chazeron, Pierre-Michel Llorca & Georges Brousse - 2022 - Frontiers in Psychology 13.
    ContextThe recent development of “serious games” has produced encouraging results in maintaining adherence to health-related interventions. In alcohol research, several studies have shown that computerized training on attentional bias decreases alcohol consumption bias among students. However, these highly controlled experimental situations, do not allow for direct large-scale dissemination. Our objective is to evaluate an attentional bias remediation program using a gamified smartphone training procedure.MethodsFifty students from Clermont-Ferrand University were invited to participate in the study. After a cognitive (...)
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  14.  19
    Bias in the Evaluation of Conflict of Interest Policies.Zachariah Sharek, Robert E. Schoen & George Loewenstein - 2012 - Journal of Law, Medicine and Ethics 40 (2):368-382.
    Physicians are affected by the conflict of interest (COI) policies they help formulate. This study examines whether physicians evaluate these policies impartially. One hundred and seventy-nine physicians, 224 financial advisors, and 1,430 members of the general public evaluated the fairness and efficacy of a COI policy in either a medical or financial context. Physicians were more critical of the medical COI policy compared to a financial COI policy, while financial professionals displayed the reverse pattern and control respondents rated both policies (...)
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  15.  11
    Bias in the Evaluation of Conflict of Interest Policies.Zachariah Sharek, Robert E. Schoen & George Loewenstein - 2012 - Journal of Law, Medicine and Ethics 40 (2):368-382.
    A wide range of medical institutions have developed and implemented policies to mitigate the adverse consequences of conflicts of interest. These newly implemented policies, which include regulation of industry contact with physicians and hospitals, controls on gifts from industry, and greater transparency in industry sponsored activities, have generated considerable controversy.Formulating and evaluating policies in a neutral, unbiased fashion can be difficult for those personally affected. When people have a stake in an issue, they tend to process information in a selective (...)
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  16.  24
    Evaluating causes of algorithmic bias in juvenile criminal recidivism.Marius Miron, Songül Tolan, Emilia Gómez & Carlos Castillo - 2020 - Artificial Intelligence and Law 29 (2):111-147.
    In this paper we investigate risk prediction of criminal re-offense among juvenile defendants using general-purpose machine learning algorithms. We show that in our dataset, containing hundreds of cases, ML models achieve better predictive power than a structured professional risk assessment tool, the Structured Assessment of Violence Risk in Youth, at the expense of not satisfying relevant group fairness metrics that SAVRY does satisfy. We explore in more detail two possible causes of this algorithmic bias that are related to biases (...)
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  17.  4
    Lay Evaluation of Financial Experts: The Action Advice Effect and Confirmation Bias.Tomasz Zaleskiewicz, Agata Gasiorowska, Katarzyna Stasiuk, Renata Maksymiuk & Yoram Bar-Tal - 2016 - Frontiers in Psychology 7.
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  18.  22
    Expectancy bias mediates the link between social anxiety and memory bias for social evaluation.Justin D. Caouette, Sarah K. Ruiz, Clinton C. Lee, Zainab Anbari, Roberta A. Schriber & Amanda E. Guyer - 2015 - Cognition and Emotion 29 (5):945-953.
  19.  6
    Gender Bias in the Evaluation of Teaching Materials.Asri Özgümüs, Holger A. Rau, Stefan T. Trautmann & Christian König-Kersting - 2020 - Frontiers in Psychology 11.
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  20.  10
    Response-bias interpretation of "Perceptual Defense." A selective review and an evaluation of recent research.James G. Minard - 1965 - Psychological Review 72 (1):74-88.
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  21. Implicit Bias, Character and Control.Jules Holroyd & Daniel Kelly - 2016 - In Alberto Masala & Jonathan Webber (eds.), From Personality to Virtue: Essays on the Philosophy of Character. Oxford: Oxford University Press UK. pp. 106-133.
    Our focus here is on whether, when influenced by implicit biases, those behavioural dispositions should be understood as being a part of that person’s character: whether they are part of the agent that can be morally evaluated.[4] We frame this issue in terms of control. If a state, process, or behaviour is not something that the agent can, in the relevant sense, control, then it is not something that counts as part of her character. A number of theorists have argued (...)
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  22.  49
    Reducing normative bias in health technology assessment: Interactive evaluation and casuistry.Rob P. B. Reuzel, Gert-Jan van Der Wilt, Henk A. M. J. ten Have & Pieter F. de Vries Robbé - 1999 - Medicine, Health Care and Philosophy 2 (3):255-263.
    Health technology assessment (HTA) is often biased in the sense that it neglects relevant perspectives on the technology in question. To incorporate different perspectives in HTA, we should pursue agreement about what are relevant, plausible, and feasible research questions; interactive technology assessment (iTA) might be suitable for this goal. In this way a kind of procedural ethics is established. Currently, ethics too often is focussed on the application of general principles, which leaves a lot of confusion as to what really (...)
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  23.  39
    Role of Hindsight Bias, Ethics, and Self-Other Judgments in Students’ Evaluation of an Animal Experiment.Harry L. Hom & Donn L. Kaiser - 2016 - Ethics and Behavior 26 (1):1-13.
    Does hindsight knowledge make research seem more ethical and predictable? In line with the notion of hindsight bias, students in 3 experiments knowing the outcome of an animal experiment judged the results as more foreseeable and ethical relative to students who did not know the outcome. Via self to other comparisons, students evaluate themselves more favorably compared to a peer but exhibited hindsight bias in doing so. Uniquely, the findings reveal the possibility that students deem themselves to be (...)
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  24.  6
    Reducing normative bias in health technology assessment: Interactive evaluation and casuistry.Rob Reuzel, Gert-jan van der Wilt, Henk ten Have & Pieter de Vries Robbé - 1999 - Medicine, Health Care and Philosophy 2 (3):255-263.
    Health technology assessment (HTA) is often biased in the sense that it neglects relevant perspectives on the technology in question. To incorporate different perspectives in HTA, we should pursue agreement about what are relevant, plausible, and feasible research questions; interactive technology assessment (iTA) might be suitable for this goal. In this way a kind of procedural ethics is established. Currently, ethics too often is focussed on the application of general principles, which leaves a lot of confusion as to what really (...)
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  25.  13
    Affective Language, Interpretation Bias and Its Molecular Genetic Variations: Exploring the Relationship Between Genetic Variations of the OXTR Gene and the Emotional Evaluation of Words Related to the Self or the Other.Friedrich Meixner, Christian Montag & Cornelia Herbert - 2019 - Frontiers in Psychology 10.
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  26.  11
    Two sources of bias affecting the evaluation of autistic communication.Pearl Han Li & Melissa Koenig - 2019 - Behavioral and Brain Sciences 42.
    We support Jaswal & Akhtar's interrogation of social motivational accounts of autism and discuss two sources of bias that contribute to how others construe autistic people's communications: an experience-based bias that limits our ability to discern the speaker's action as communicative and a prejudice against the credibility of certain speakers that limits a listener's willingness to believe their testimony.
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  27.  56
    Is present-bias a distinctive psychological kind?Natalja Deng, Batoul Hodroj, Andrew J. Latham, Jordan Lee-Tory & Kristie Miller - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    Present-bias is the preference, all else being equal, for positive events to be located in the present rather than the non-present, and for negative events to be located in the non-present rather than the present. Very little attention has been given to present-bias in the contemporary literature on time biases. This may be because it is often assumed that present-bias is not a distinctive psychological kind; that what explains people’s being present-biased is just what explains them displaying (...)
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  28.  30
    Culture and Social Desirability Bias: Ethical Evaluations by Chinese and Canadian Business Students.Paul Dunn & Anamitra Shome - 2007 - Proceedings of the International Association for Business and Society 18:12-14.
    This study finds cultural divergence among business students from Canada and the People’s Republic of China. The Chinese and Canadian students, regardless of gender, exhibit different ethical attitudes towards questionable business practices. Also, the Canadian students, especially the women, demonstrate a stronger social desirability bias (a tendency to deny socially unacceptable actions and to admit to socially desirable ones) than do the Chinese business students. Finally, this bias causes respondents to increase their assessment of the un-ethicality of questionable (...)
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  29.  17
    Responding to Implicit Bias in Abusive Head Trauma Evaluations and Reporting in the PICU: Ethical Consideration During a Clinical Trial.Kent P. Hymel & Jennifer B. McCormick - 2019 - American Journal of Bioethics 19 (10):114-115.
    Volume 19, Issue 10, October 2019, Page 114-115.
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  30.  18
    Development and evaluation of a new paradigm for the assessment of anxiety-disorder-specific interpretation bias using picture stimuli.Tina In-Albon, Anke Klein, Mike Rinck, Eni Becker & Silvia Schneider - 2008 - Cognition and Emotion 22 (3):422-436.
  31. Implicit bias, confabulation, and epistemic innocence.Ema Sullivan-Bissett - 2014 - Consciousness and Cognition 33:548-560.
    In this paper I explore the nature of confabulatory explanations of action guided by implicit bias. I claim that such explanations can have significant epistemic benefits in spite of their obvious epistemic costs, and that such benefits are not otherwise obtainable by the subject at the time at which the explanation is offered. I start by outlining the kinds of cases I have in mind, before characterising the phenomenon of confabulation by focusing on a few common features. Then I (...)
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  32.  44
    Sex Drugs and Corporate Ventriloquism: How to Evaluate Science Policies Intended to Manage Industry-Funded Bias.Bennett Holman & Sally Geislar - 2018 - Philosophy of Science 85 (5):869-881.
    “Female sexual dysfunction” is the type of contested disease that has sparked concern about the role of the pharmaceutical industry in medical science. Many policies have been proposed to manage industry influence without carefully evaluating whether the proposed policies would be successful. We consider a proposal for incorporating citizen stakeholders into scientific research and show, via a detailed case study of the pharmaceutical regulation of flibanserin, that such programs can be co-opted. In closing, we use Holman’s asymmetric arms race framework (...)
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  33.  13
    Good decision vs. good results: Outcome bias in the evaluation of financial agents.Christian König-Kersting, Monique Pollmann, Jan Potters & Stefan T. Trautmann - 2020 - Theory and Decision 90 (1):31-61.
    We document outcome bias in situations where an agent makes risky financial decisions for a principal. In three experiments, we show that the principal’s evaluations and financial rewards for the agent are strongly affected by the random outcome of the risky investment. This happens despite her exact knowledge of the investment strategy, which can, therefore, be assessed independently of the outcome. The principal thus judges the same decision by the agent differently, depending on factors that the agent has no (...)
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  34. Disambiguating Algorithmic Bias: From Neutrality to Justice.Elizabeth Edenberg & Alexandra Wood - 2023 - In Francesca Rossi, Sanmay Das, Jenny Davis, Kay Firth-Butterfield & Alex John (eds.), AIES '23: Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society. Association for Computing Machinery. pp. 691-704.
    As algorithms have become ubiquitous in consequential domains, societal concerns about the potential for discriminatory outcomes have prompted urgent calls to address algorithmic bias. In response, a rich literature across computer science, law, and ethics is rapidly proliferating to advance approaches to designing fair algorithms. Yet computer scientists, legal scholars, and ethicists are often not speaking the same language when using the term ‘bias.’ Debates concerning whether society can or should tackle the problem of algorithmic bias are (...)
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  35. Bias towards the future.Kristie Miller, Preston Greene, Andrew J. Latham, James Norton, Christian Tarsney & Hannah Tierney - 2022 - Philosophy Compass 17 (8):e12859.
    All else being equal, most of us typically prefer to have positive experiences in the future rather than the past and negative experiences in the past rather than the future. Recent empirical evidence tends not only to support the idea that people have these preferences, but further, that people tend to prefer more painful experiences in their past rather than fewer in their future (and mutatis mutandis for pleasant experiences). Are such preferences rationally permissible, or are they, as time-neutralists contend, (...)
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  36.  99
    Commensuration Bias in Peer Review.Carole J. Lee - 2015 - Philosophy of Science 82 (5):1272-1283,.
    To arrive at their final evaluation of a manuscript or grant proposal, reviewers must convert a submission’s strengths and weaknesses for heterogeneous peer review criteria into a single metric of quality or merit. I identify this process of commensuration as the locus for a new kind of peer review bias. Commensuration bias illuminates how the systematic prioritization of some peer review criteria over others permits and facilitates problematic patterns of publication and funding in science. Commensuration bias (...)
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  37. Hindsight bias is not a bias.Brian Hedden - 2019 - Analysis 79 (1):43-52.
    Humans typically display hindsight bias. They are more confident that the evidence available beforehand made some outcome probable when they know the outcome occurred than when they don't. There is broad consensus that hindsight bias is irrational, but this consensus is wrong. Hindsight bias is generally rationally permissible and sometimes rationally required. The fact that a given outcome occurred provides both evidence about what the total evidence available ex ante was, and also evidence about what that evidence (...)
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  38.  56
    Cultural Crossvergence and Social Desirability Bias: Ethical Evaluations by Chinese and Canadian Business Students.Paul Dunn & Anamitra Shome - 2009 - Journal of Business Ethics 85 (4):527-543.
    The purpose of this study is to determine whether there are cross-cultural differences between Chinese and Canadian business students with respect to their assessment of the ethicality of various business behaviors. Using a sample of 147 business students, the results indicate cultural crossvergence; the Chinese (72 students) and Canadians (75 students) exhibit different ethical attitudes toward questionable business practices at the individual level but not at the corporate level. A social desirability bias (a tendency to deny socially unacceptable actions (...)
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  39. Algorithmic bias: on the implicit biases of social technology.Gabbrielle M. Johnson - 2020 - Synthese 198 (10):9941-9961.
    Often machine learning programs inherit social patterns reflected in their training data without any directed effort by programmers to include such biases. Computer scientists call this algorithmic bias. This paper explores the relationship between machine bias and human cognitive bias. In it, I argue similarities between algorithmic and cognitive biases indicate a disconcerting sense in which sources of bias emerge out of seemingly innocuous patterns of information processing. The emergent nature of this bias obscures the (...)
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  40.  25
    Does “putting on your thinking cap” reduce myside bias in evaluation of scientific evidence?Caitlin Drummond & Baruch Fischhoff - 2019 - Thinking and Reasoning 25 (4):477-505.
    The desire to maintain current beliefs can lead individuals to evaluate contrary evidence more critically than consistent evidence. We test whether priming individuals’ scientific reasoning...
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  41.  88
    Implicit bias in healthcare professionals: a systematic review.Chloë FitzGerald & Samia Hurst - 2017 - BMC Medical Ethics 18 (1):19.
    Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines the evidence that healthcare professionals display implicit biases towards patients. PubMed, PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. Two reviewers assessed the eligibility of the identified papers based on precise content and quality criteria. The references of eligible papers (...)
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  42.  89
    Exploring social desirability bias.Janne Chung & Gary S. Monroe - 2003 - Journal of Business Ethics 44 (4):291 - 302.
    This study examines social desirability bias in the context of ethical decision-making by accountants. It hypothesizes a negative relation between social desirability bias and ethical evaluation. It also predicts an interaction effect between religiousness and gender on social desirability bias. An experiment using five general business vignettes was carried out on 121 accountants (63 males and 58 females). The results show that social desirability bias is higher (lower) when the situation encountered is more (less) unethical. (...)
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  43.  17
    Causal diagrams for encoding and evaluation of information bias.Eyal Shahar - 2009 - Journal of Evaluation in Clinical Practice 15 (3):436-440.
  44. Diagnosing bias in philosophy of religion.Paul Draper & Ryan Nichols - 2013 - The Monist 96 (3):420-446.
    Work in philosophy of religion exhibits at least four symptoms of poor health: it is too partisan, too polemical, too narrow in its focus, and too often evaluated using criteria that are theological or religious instead of philosophical. Our diagnosis is that, because of the emotional and psychosocial aspects of religion, many philosophers of religion suffer from cognitive biases and group influence. We support this diagnosis in two ways. First, we examine work in psychology on cognitive biases and their affective (...)
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  45.  80
    Cognitive bias in rats is not influenced by oxytocin.Molly C. McGuire, Keith L. Williams, Lisa L. M. Welling & Jennifer Vonk - 2015 - Frontiers in Psychology 6:152615.
    The effect of oxytocin on cognitive bias was investigated in rats in a modified conditioned place preference (CPP) paradigm. Fifteen male rats were trained to discriminate between two different cue combinations, one paired with palatable foods (reward training), and the other paired with unpalatable food (aversive training). Next, their reactions to two ambiguous cue combinations were evaluated and their latency to contact the goal pot recorded. Rats were injected with either oxytocin (OT) or saline with the prediction that rats (...)
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  46. Implicit Bias and Philosophy, Volume 2: Moral Responsibility, Structural Injustice, and Ethics.Michael Brownstein & Jennifer Saul (eds.) - 2016 - Oxford, GB: Oxford University Press UK.
    There is abundant evidence that most people, often in spite of their conscious beliefs, values and attitudes, have implicit biases. 'Implicit bias' is a term of art referring to evaluations of social groups that are largely outside conscious awareness or control. These evaluations are typically thought to involve associations between social groups and concepts or roles like 'violent,' 'lazy,' 'nurturing,' 'assertive,' 'scientist,' and so on. Such associations result at least in part from common stereotypes found in contemporary liberal societies (...)
     
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  47.  50
    Myside bias in thinking about abortion.Jonathan Baron - 1995 - Thinking and Reasoning 1 (3):221 – 235.
    College-student subjects made notes about the morality of early abortion, as if they were preparing for a class discussion. Analysis of the quality of their arguments suggests that a distinction can be made between arguments based on well-supported warrants and those based on warrants that are easily criticised. The subjects also evaluated notes made by other, hypothetical, students preparing for the same discussion. Most subjects evaluated the set of arguments as better when the arguments were all on one side than (...)
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  48.  5
    A Pictorial Dot Probe Task to Assess Food-Related Attentional Bias in Youth With and Without Obesity: Overview of Indices and Evaluation of Their Reliability.Leentje Vervoort, Maya Braun, Maarten De Schryver, Tiffany Naets, Ernst H. W. Koster & Caroline Braet - 2021 - Frontiers in Psychology 12.
    Several versions of the dot probe detection task are frequently used to assess maladaptive attentional processes associated with a broad range of psychopathology and health behavior, including eating behavior and weight. However, there are serious concerns about the reliability of the indices derived from the paradigm as measurement of attentional bias toward or away from salient stimuli. The present paper gives an overview of different attentional bias indices used in psychopathology research and scrutinizes three types of indices calculated (...)
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  49. Implicit Bias and Prejudice.Jules Holroyd & Kathy Puddifoot - 2019 - In M. Fricker, N. J. L. L. Pedersen, D. Henderson & P. J. Graham (eds.), Routledge Handbook of Social Epistemology. Routledge.
    Recent empirical research has substantiated the finding that very many of us harbour implicit biases: fast, automatic, and difficult to control processes that encode stereotypes and evaluative content, and influence how we think and behave. Since it is difficult to be aware of these processes - they have sometimes been referred to as operating 'unconsciously' - we may not know that we harbour them, nor be alert to their influence on our cognition and action. And since they are difficult to (...)
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  50.  74
    Is future bias a manifestation of the temporal value asymmetry?Eugene Caruso, Andrew J. Latham & Kristie Miller - forthcoming - Philosophical Psychology.
    Future-bias is the preference, all else being equal, for positive states of affairs to be located in the future not the past, and for negative states of affairs to be located in the past not the future. Three explanations for future-bias have been posited: the temporal metaphysics explanation, the practical irrelevance explanation, and the three mechanisms explanation. Understanding what explains future-bias is important not only for better understanding the phenomenon itself, but also because many philosophers think that (...)
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