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Books on the topic 'Bias cognitivi'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 March 2023

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1

James, Ree Malcolm, and Air Force Research Laboratory (Wright-Patterson Air Force Base, Ohio). Warfighter Training Research Division, eds. Near identity of cognitive structure in sex and ethnic groups. Mesa, AZ: Air Force Materiel Command, Air Force Research Laboratory, Human Effectiveness Directorate, Warfighter Training Research Division, 1998.

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2

Owen, K. Test and item bias: The suitability of the Junior aptitude tests as a common test battery for White, Indian, and Black pupils in standard 7. Pretoria: Human Sciences Research Council, 1989.

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3

1956-, Gross Paget H., ed. How do journalists think?: A proposal for the study of cognitive bias in newsmaking. Bloomington, IN: ERIC Clearinghouse on Reading and Communication Skills, Smith Research Center, Indiana University, 1989.

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4

Yu yi de bian hua zhuan huan yan jiu: Ci gai nian kuang jia shi jiao. Changsha Shi: Hunan shi fan da xue chu ban she, 2011.

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5

Ci gai nian kuang jia yuan su de yu yan xing shi biao zheng yan jiu: A study on the linguistic formal representation of lexical concept frames' elements. Beijing: Guang ming ri bao chu ban she, 2011.

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6

Jimao, Guo, and Zheng Tian'gang, eds. Si tong shi yi: Han yu jin yi biao da fang shi de ren zhi yu yong fen xi=Sitong shiyi /cGuo Jimao, Zheng Tian'gang zhu bian. Beijing: Zhongguo she hui ke xue chu ban she, 2002.

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7

Amir, Hussain, Liu Derong, Wang Zhanshan, and SpringerLink (Online service), eds. Advances in Brain Inspired Cognitive Systems: 5th International Conference, BICS 2012, Shenyang, China, July 11-14, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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8

Liu, Derong. Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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9

Wang, Meiping. Riben dui Zhongguo de ren zhi yan bian: Cong jia wu zhan zheng dao jiu yi ba shi bian = The evolution of Japan's cognition of China. Beijing Shi: She hui ke xue wen xian chu ban she, 2021.

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10

Langer, Ellen J. Xue xi, jiu shi yi zhong xiang shou: Ni ye ke yi ba xue xi he gong zuo bian cheng "wan le" de dai ming ci. Taibei Xian Xindian Shi: Ren ben zi ran wen hua shi ye you xian gong si, 2006.

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11

author, Ju Xiaoli, and Yan Linqiong author, eds. Han Ying shu zi ren zhi biao zheng dui bi yan jiu: A CONTRASTIVE STUDY OF COGNITIVE REPRESENTATION OF NUMBER BETWEEN CHINESE AND ENGLISH. Zhenjiang Shi: Jiangsu da xue chu ban she, 2011.

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12

Aronson, Elliot. Mistakes Were Made (But Not by Me): Why we Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts. Orlando FL, USA: Harcourt, 2007.

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13

Ren lei gan zhi he shi ying qi hou bian hua de xing wei xue yan jiu: Yi Jilin Sheng Dunhua Shi xiang cun wei li = Behavioral science based research on human cognition and adaptation to climate change : a case study on rural area in Dunhua City, Jilin Province. Beijing: Zhongguo huan jing ke xue chu ban she, 2011.

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14

Zhao, Xiufeng. A cognitive approach to discourse perspective representation: Reference as perspective marker in stream-of-consciousness discourse = [Yu pian shi jiao yu yan biao zheng de ren zhi yan jiu : zhi cheng zai yi shi liu yu pian zhong de shi jiao biao zhi zuo yong]. Beijing: Ke xue chu ban she, 2009.

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15

2050 ke huan da cheng zhen: Chao neng li, xin zhi kong zhi, ren zao ji yi, yi wang yao wan, nai mi ji qi ren ji jiang gai bian wo men de shi jie. Taibei Shi: Shi bao wen hua chu ban qi ye gu fen you xian gong si, 2015.

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16

Qian, Bingyi. Ming Qing shi qi dui Yunnan min zu ren zhi de yan jin yu bian jiang zhi li: A study of the cognitive evolution of Yunnan's ethnic groups in Ming and Qing dyansties and the governance of frontier areas in southwestern China. Beijing: She hui ke xue wen xian chu ban she, 2019.

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17

Faranda, Massimo. Neuromarketing: Sfruttare I Bias Cognitivi e la Comunicazione Persuasiva per Vendere Qualsiasi Cosa. Independently Published, 2021.

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18

Mariani, Francesco. Neuromarketing: Il Processo Decisionale Del Cliente, I Fattori Che lo Influenzano, la Teoria Dei Tre Cervelli, il Ruolo Delle Emozioni, Bias Cognitivi, Neuromarketing in Pratica e Molto Altro! Independently Published, 2020.

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19

Thomas, David Dylan. DESIGN FOR COGNITIVE BIAS. A BOOK APART, 2020.

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20

Whitesmith, Martha. Cognitive Bias in Intelligence Analysis. Edinburgh University Press, 2020. http://dx.doi.org/10.3366/edinburgh/9781474466349.001.0001.

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Belief, Bias and Intelligence outlines an approach for reducing the risk of cognitive biases impacting intelligence analysis that draws from experimental research in the social sciences. It critiques the reliance of Western intelligence agencies on the use of a method for intelligence analysis developed by the CIA in the 1990’s, the Analysis of Competing Hypotheses (ACH). The book shows that the theoretical basis of the ACH method is significantly flawed, and that there is no empirical basis for the use of ACH in mitigating cognitive biases. It puts ACH to the test in an experimental setting against two key cognitive biases with unique empirical research facilitated by UK’s Professional Heads of Intelligence Analysis unit at the Cabinet Office, includes meta-analysis into which analytical factors increase and reduce the risk of cognitive bias and recommends an alternative approach to risk mitigation for intelligence communities. Finally, it proposes alternative models for explaining the underlying causes of cognitive biases, challenging current leading theories in the social sciences.

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21

Whitesmith, Martha. Cognitive Bias in Intelligence Analysis. Edinburgh University Press, 2020. http://dx.doi.org/10.1515/9781474466363.

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22

Bias In Human Reasoning (Essays in Cognitive Psychology). Psychology Press, 1990.

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23

Priest, Henry. Beating Biases: Overcoming Cognitive Bias and Improving Decisions. Independently Published, 2019.

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24

Kenski, Kate. Overcoming Confirmation and Blind Spot Biases When Communicating Science. Edited by Kathleen Hall Jamieson, Dan M. Kahan, and Dietram A. Scheufele. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190497620.013.40.

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This chapter focuses on two biases that lead people away from evaluating evidence and scientific studies impartially—confirmation bias and bias blind spot. The chapter first discusses different ways in which people process information and reviews the costs and benefits of utilizing cognitive shortcuts in decision making. Next, two common cognitive biases, confirmation bias and bias blind spot, are explained. Then the literature on “debiasing” is explored. Finally, the implications of confirmation bias and bias blind spot in the context of communicating about science are examined, and an agenda for future research on understanding and mitigating these biases is offered.

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25

Durmus, Murat. COGNITIVE BIASES - a Brief Overview of over 160 Cognitive Biases : + Bonus Chapter: Algorithmic Bias. Lulu Press, Inc., 2022.

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26

Cole, Ben. Syrian Information and Propaganda War: The Role of Cognitive Bias. Springer International Publishing AG, 2022.

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27

Applying Behavioral Finance to Investing: Cognitive Bias and market anomalies. LAP Lambert Academic Publishing, 2012.

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28

Brian, Freemantle. BIAS IN HUMAN REASON:SEE PB ED (Essays in Cognitive Psychology). Psychology Press, 1989.

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29

Braman, Eileen. Cognition in the Courts. Edited by Lee Epstein and Stefanie A. Lindquist. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199579891.013.31.

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This chapter critically evaluates how experiments are used to study cognitive processes involved in legal reasoning. Looking at research on legal presumptions, heuristic processing, and various types of bias in judicial decision-making, the analysis considers how experiments with judges, lay participants, and other legally trained populations have contributed to our understanding of the psychological processes involved in fact-finding and legal decision-making. It explores how behavioral economics, dual process models, cultural cognition, and motivated reasoning frameworks have been used to inform experimental research. The chapter concludes with a discussion of what findings add to our normative understanding of issues like accuracy and neutrality in decision-making and a call to better integrate knowledge gained through experimental methods across disciplinary boundaries.

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30

Zwieback, Dave. Human Side of Postmortems: Managing Stress and Cognitive Bias in Devops. O'Reilly Media, Incorporated, 2013.

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31

Soroka, Stuart N. Gatekeeping and the Negativity Bias. Oxford University Press, 2016. http://dx.doi.org/10.1093/acrefore/9780190228637.013.43.

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Research on media gatekeeping is focused on the factors leading to a distribution of information in media content that is systematically different from the “real world.” Early gatekeeping work examined editorial decisions, and emphasized the effect that a single editor’s preferences and beliefs could have on the content new consumers receive. The literature has gradually shifted to focus on more generalizable factors, however. These include organization-level assessments of newsworthiness and commercial/economic considerations; broader system-level factors including the impact of dominant ideologies and political and social norms; and common individual-level factors, including a range of cognitive and psychological biases.The tendency for humans to prioritize negative over positive information is one such cognitive bias—and the growing literature on the negativity bias is discussed here as one example of a set of organization-, system-, and individual-level “gates” that have a systematic impact on news content. Negativity is just one example, however. Sensationalism, violence, geographic proximity, availability of visuals, prominence of celebrities—all of these tendencies in media content can and have been examined effectively using the gatekeeping metaphor. Some of this work is reviewed here, alongside some recent trends in gatekeeping work, including the “distributional” approach to gatekeeping, and the shift in gatekeeping brought on by the “new media” environment.

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32

Hardy, Bruce W., and Kathleen Hall Jamieson. Overcoming Biases in Processing of Time Series Data About Climate. Edited by Kathleen Hall Jamieson, Dan M. Kahan, and Dietram A. Scheufele. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190497620.013.43.

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This chapter notes the important ways in which time series data are used in science, explains how trend lines are created and reported, chronicles ways in which they can be misused, documents human biases that lead to overvaluing endpoints in a trend, and outlines ways to minimize that bias. Specifically, this chapter defines trend lines and time series data and explain why and how they matter in science communication. A discussion on cognitive biases that influence interpretations of trend lines, such as endpoint bias and peak and end rule, recency bias, accessibility bias, and extrapolation bias, is offered as are communication tools scientists, journalists, and other science communicators can use to overcome these biases.

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33

Lichter, S. Robert. Theories of Media Bias. Edited by Kate Kenski and Kathleen Hall Jamieson. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199793471.013.44.

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Ideological or partisan media bias is widely debated despite disagreement about its meaning, measurement, and impact. The assumption that news should be objective is itself the object of considerable debate. Assertions of a conservative or establishment bias in the news often draw on critical theory, which argues that news preserves the hegemony of society’s ruling interests. Assertions of liberal bias draw on surveys of journalists’ attitudes and content analyses of news coverage. This case has recently been bolstered by economic modeling. However, numerous content analytic studies have failed to find a liberal bias. This has led to efforts to explain public perceptions of liberal bias in terms of cognitive psychology and elite manipulation. Other explanations include structural biases and media negativism. Internet-driven changes in journalism, including an increase in partisan news, may force a rethinking of the entire debate or even render it irrelevant.

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34

Lichter, S. Robert. Theories of Media Bias. Edited by Kate Kenski and Kathleen Hall Jamieson. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199793471.013.44_update_001.

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Ideological or partisan media bias is widely debated despite disagreement about its meaning, measurement, and impact. The assumption that news should be objective is itself the object of considerable debate. Assertions of a conservative or establishment bias in the news often draw on critical theory, which argues that news preserves the hegemony of society’s ruling interests. Assertions of liberal bias draw on surveys of journalists’ attitudes and content analyses of news coverage. This case has recently been bolstered by economic modeling. However, numerous content analytic studies have failed to find a liberal bias. This has led to efforts to explain public perceptions of liberal bias in terms of cognitive psychology and elite manipulation. Other explanations include structural biases and media negativism. Internet-driven changes in journalism, including an increase in partisan news, may force a rethinking of the entire debate or even render it irrelevant.

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35

Whitesmith, Martha. Cognitive Bias in Intelligence Analysis: Testing the Analysis of Competing Hypotheses Method. Edinburgh University Press, 2020.

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36

Vernooij, Cornell, Judith Stuijt, Steven Ten Have, Wouter ten Have, and Maarten Hendriks. Organizational Behaviour and Change Management: The Impact of Cognitive and Social Bias. Routledge, 2022.

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37

Organizational Behaviour and Change Management: The Impact of Cognitive and Social Bias. Taylor & Francis Group, 2022.

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38

Vernooij, Cornell, Judith Stuijt, Steven ten Have, Wouter ten Have, and Maarten Hendriks. Organizational Behaviour and Change Management: The Impact of Cognitive and Social Bias. Taylor & Francis Group, 2022.

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39

Whitesmith, Martha. Cognitive Bias in Intelligence Analysis: Testing the Analysis of Competing Hypotheses Method. Edinburgh University Press, 2022.

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40

Whitesmith, Martha. Cognitive Bias in Intelligence Analysis: Testing the Analysis of Competing Hypotheses Method. Edinburgh University Press, 2020.

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41

Whitesmith, Martha. Cognitive Bias in Intelligence Analysis: Testing the Analysis of Competing Hypotheses Method. Edinburgh University Press, 2020.

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42

Vernooij, Cornell, Judith Stuijt, Steven Ten Have, Wouter ten Have, and Maarten Hendriks. Organizational Behaviour and Change Management: The Impact of Cognitive and Social Bias. Routledge, 2022.

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43

Vernooij, Cornell, Judith Stuijt, Steven ten Have, Wouter ten Have, and Maarten Hendriks. Organizational Behaviour and Change Management: The Impact of Cognitive and Social Bias. Taylor & Francis Group, 2022.

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44

Streiner, David L., Geoffrey R. Norman, and John Cairney. Biases in responding. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199685219.003.0006.

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Scale constructors hope that people will respond to the items by giving thoughtful and honest answers to every item. However, there are many biases that conspire against this, including end-aversion bias, social desirability bias, yea- and nay-saying, and others. The chapter discusses the different perspectives of the scale constructor and the respondent, and how this leads to some forms of bias. Answering questions is not as easy as we may imagine; there are many cognitive demands imposed by doing so, and these, too, can introduce other biases. The chapter also covers the effects of framing (how the question is worded), as well as the difficulties that are encountered in attempting to measure change. Finally, it discusses various ways of conducting cognitive interviews to ensure that the questions are being responded to as accurately as possible.

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45

Pohl, Rüdiger F. Cognitive Illusions: A Handbook on Fallacies and Biases in Thinking, Judgement and Memory. Taylor & Francis Group, 2012.

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46

Cognitive Illusions: A Handbook on Fallacies and Biases in Thinking, Judgement and Memory. Taylor & Francis Group, 2016.

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47

Pohl, Rüdiger F. Cognitive Illusions: Intriguing Phenomena in Judgement, Thinking and Memory. Taylor & Francis Group, 2016.

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48

Pohl, Rüdiger F. Cognitive Illusions: Intriguing Phenomena in Judgement, Thinking and Memory. Taylor & Francis Group, 2022.

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49

Pohl, Rüdiger F. Cognitive Illusions: Intriguing Phenomena in Judgement, Thinking and Memory. Taylor & Francis Group, 2016.

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50

Pohl, Rüdiger F. Cognitive Illusions: Intriguing Phenomena in Judgement, Thinking and Memory. Taylor & Francis Group, 2016.

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