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1

Burchell, Brendan Joseph. Confirmation bias and the testing of hypotheses about other people. [s.l.]: typescript, 1986.

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2

Baranova, Ivanna. Confirmation Bias. Metatron Press, 2019.

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3

Acks, Alex. Bubble of Confirmation Bias. Enslow Publishing, LLC, 2018.

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Acks, Alex. Bubble of Confirmation Bias. Enslow Publishing, LLC, 2018.

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5

Bubble of Confirmation Bias. Enslow Publishing, LLC, 2018.

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6

Kenski, Kate. Overcoming Confirmation and Blind Spot Biases When Communicating Science. Herausgegeben von Kathleen Hall Jamieson, Dan M. Kahan und 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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7

Stegenga, Jacob. Bias and Fraud. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198747048.003.0010.

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There are numerous biases in medical research that render evidence from such research systematically misleading. Some of these biases are exacerbated by conflicts of interest, including fantastic financial incentives. The most important biases in medical research include confirmation bias, design bias, analysis bias, and publication bias. Arguably, some forms of bias, such as publication bias, should be considered as fraud. The pervasiveness of bias in medical research justifies one of the premises of the master argument for medical nihilism. Medical research is malleable due to the many biases, and such malleability allows for the production of evidence that suggests medical interventions are effective, whether or not they are in fact effective.
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8

Silliman, Brian, und Stephanie Wear. Conservation bias: What have we learned? Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198808978.003.0028.

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Conservation science is unique among scientific disciplines in that it was founded on a set of normative principles. The often dogmatic adherence to these principles has made conservation science vulnerable to confirmation bias. When confronted with data, many foundational ideas in conservation, such as all nonnative species are bad, reserves are the best method to save nature, and biodiversity is declining locally, are found to be inconsistent or inaccurate. Evaluation of the validity of these ideas, however, is not crippling. Instead critical evaluation provides opportunities to learn and pivot to take advantage of new opportunities. These new conservation frontiers include planning to co-exist with nature in addition to protecting nature from humans, and creating novel and hybrid ecosystems in addition to restoring ecosystems to a pristine state. The future holds great promise for nature to expand and thrive if data are used to correct biases and conservation practices are adjusted accordingly.
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9

Hulse, Carl. Confirmation Bias: Inside Washington's War over the Supreme Court, from Scalia's Death to Justice Kavanaugh. HarperCollins Publishers, 2020.

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10

Confirmation Bias: Inside Washington's War Over the Supreme Court, from Scalia's Death to Justice Kavanaugh. Harper, 2019.

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11

Confirmation Bias: Inside Washington's War over the Supreme Court, from Scalia's Death to Justice Kavanaugh. HarperCollins Publishers, 2020.

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12

Dane, Charlotte. Cornelius Learns About Confirmation Bias: A Children's Book About Being Open-Minded and Listening to Others. PKCS Media, 2021.

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13

Dane, Charlotte. Cornelius Learns about Confirmation Bias: A Children's Book about Being Open-Minded and Listening to Others. PKCS Media, 2021.

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14

Silliman, Brian R., Brent B. Hughes, Y. Stacy Zhang und Qiang He. Business as usual leads to underperformance in coastal restoration. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198808978.003.0027.

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This chapter shows that coastal wetland projects are underperforming because of confirmation bias. Despite two decades of work showing that top-down control can be essential to marsh restoration, the potential role of top predators is typically ignored by those responsible for restoring or maintaining marshes. Similarly ignored are experiments that indicate positive interaction between marsh plants and can enhance the pace and success of restoration. By planting marsh plants at higher densities, marsh restoration success can double, and seagrass restoration can succeed in the face of increasing drought and eutrophication effects. Continued failure to integrate top-down control and facilitative species interactions into coastal restoration designs will result in widespread underperformance of wetland conservation projects and unrealized generation of important ecosystem services.
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15

Lacewing, Michael. Could Psychoanalysis be a Science? Herausgegeben von K. W. M. Fulford, Martin Davies, Richard G. T. Gipps, George Graham, John Z. Sadler, Giovanni Stanghellini und Tim Thornton. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199579563.013.0064.

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Could psychoanalysis be a science? There are three ways of reading this question. First, is psychoanalysis the kind of investigation or activity that could, logically speaking, be "scientific"? If we can defend a positive answer here, then it makes sense to ask, second, is psychoanalysis, in the form in which it has traditionally been practiced, and continues to be practiced, a science? If there are good reasons to doubt its credentials, then we might ask, third, is psychoanalysis able to become a science? This is a question about what is needed for the necessary transformation. The chapter argues that psychoanalysis can be a science, but that the historical debate raised important challenges to its methodology, viz., confirmation bias, suggestion, and unsupportable causal inference. The chapter argues that recent developments meet these challenges, and concludes with some reflections on the interdisciplinary nature of psychoanalysis.
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16

Van Swol, Lyn M., Jihyun Esther Paik und Andrew Prahl. Advice Recipients. Herausgegeben von Erina L. MacGeorge und Lyn M. Van Swol. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190630188.013.2.

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This chapter examines the psychology of advice recipients, focusing on research predominantly conducted using the Judge Advisor System, in which a participant “judge” receives advice from one or more advisors but has ultimate responsibility for making the decision. First, it reviews methods of typical Judge Advisor System experiments. Next, it surveys the research to explore why decision makers often do not seek out advice, focusing on the costs of advice and decision-maker overconfidence. It then examines why decision makers underutilize the advice they receive due to factors like confirmation bias, egocentric discounting, and power. In addition, factors that increase the utilization of advice, such as trust, advisor confidence, and advisor expertise, are considered. Finally, the influence of advice-recipient power and reception to computerized advice are examined in depth. Finally, advice to decision makers about how to seek and utilize advice to make better decisions is provided.
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17

Rudmin, Floyd, Bo Wang und Joaquim de Castro. Acculturation Research Critiques and Alternative Research Designs. Herausgegeben von Seth J. Schwartz und Jennifer Unger. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190215217.013.4.

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Dictionary definitions concur that “acculturation” means second-culture acquisition, but “acculturation” began as a Eurocentric concept that inferior peoples improve themselves by imitating superior peoples. Shadows of this persist despite the acceleration of acculturation research from nine studies per decade in the 1920s to the current rate of more than 6000 per decade. Reviews of this research have noted confused findings and lack of utility. Critics either (1) advocate for qualitative methods because culture, identity, and human experience are too complex for psychometric methods, or (2) recommend new models and new forms of quantitative analysis, or (3) fault research for poor social science practices. Rudmin (2006) has argued that academics’ shared liberal ideology causes collective confirmation bias that shapes research to promote advocacy of bicultural integration. Many future research designs and projects are proposed, including emic studies of rural-urban migration in China and the development of single-case measures of acculturative competence.
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Kareiva, Peter, Michelle Marvier und Brian Silliman, Hrsg. Effective Conservation Science. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198808978.001.0001.

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This book gathers together 28 personal stories told by leading thinkers and practitioners in conservation – all of whom have something to say about the uncomfortable tension that arises when data meet dogma. Together, they make a powerful argument for conservation science that measures effectiveness and evolves in response to new data, rather than clinging to its treasured foundational ideas. Several chapters raise doubts about some of conservation’s core tenets, including the notion that habitat fragmentation is bad for biodiversity, biodiversity declines are threatening ecosystem function, non-native species are a net negative for conservation, and fisheries management is failing. Another set of chapters warns of the potent power of conservation narratives: undeniably useful to inspire conservation action, but potentially dangerous in locking in thinking against contrary data. These chapters challenge iconic stories about GM crops, orangutans in oil palm forests, frog feminization, salmon versus dams, rehabilitating oiled otters, and wolves in Yellowstone. A final set of chapters addresses conceptual and methodological approaches such as environmental tipping points, global assessments, payment for ecosystem service programs, and working with corporations. Throughout, examples of confirmation bias emerge—not as dishonesty, but as a human foible that is a challenge for all science, not just conservation science. Graduate students, in particular, will find a wealth of ideas to inspire their own research. Each chapter points to additional data that could help resolve lingering debates and improve conservation effectiveness.
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19

Gorman, Sara E., und Jack M. Gorman. Denying to the Grave. Oxford University Press, 2016. http://dx.doi.org/10.1093/oso/9780199396603.001.0001.

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Why do some parents refuse to vaccinate their children? Why do some people keep guns at home, despite scientific evidence of risk to their family members? And why do people use antibiotics for illnesses they cannot possibly alleviate? When it comes to health, many people insist that science is wrong, that the evidence is incomplete, and that unidentified hazards lurk everywhere. In Denying to the Grave, Gorman and Gorman, a father-daughter team, explore the psychology of health science denial. Using several examples of such denial as test cases, they propose six key principles that may lead individuals to reject "accepted" health-related wisdom: the charismatic leader; fear of complexity; confirmation bias and the internet; fear of corporate and government conspiracies; causality and filling the ignorance gap; and the nature of risk prediction. The authors argue that the health sciences are especially vulnerable to our innate resistance to integrate new concepts with pre-existing beliefs. This psychological difficulty of incorporating new information is on the cutting edge of neuroscience research, as scientists continue to identify brain responses to new information that reveal deep-seated, innate discomfort with changing our minds. Denying to the Grave explores risk theory and how people make decisions about what is best for them and their loved ones, in an effort to better understand how people think when faced with significant health decisions. This book points the way to a new and important understanding of how science should be conveyed to the public in order to save lives with existing knowledge and technology.
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