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Epistemic democracy
Published in David Coady, James Chase, The Routledge Handbook of Applied Epistemology, 2018
The wisdom of the crowd view holds that wisdom or knowledge is an emergent property of the group. Though individuals within the group have inaccurate beliefs, having them vote together might cause the group as a whole to make accurate or good decisions. There are a few cases – such as guessing the number of jelly beans or the weight of farm animals – where large crowds’ mean guesses tend to be accurate. There are others cases where the mean guesses are far off. Defenders of the wisdom of the crowd view need a general theory to explain when the crowd is wise and when it is not.
Cognitive Bias Mitigation: Becoming Better Diagnosticians
Published in Pat Croskerry, Karen S. Cosby, Mark L. Graber, Hardeep Singh, Diagnosis, 2017
Sometimes the wisdom of the crowd exceeds that of an individual decision-maker [61]. Group rationality tends to exceed individual rationality [62]. Although it is time-consuming and not always practical, in complex situations, it may be worth having a case conference to reach an optimal solution, like tumor boards for example. At a minimum, it is sometimes worth bouncing one’s decision making off colleagues to run a check on one’s own thinking.
Working the literature harder: what can text mining and bibliometric analysis reveal?
Published in Expert Review of Proteomics, 2019
Yu Han, Sara A. Wennersten, Maggie P. Y. Lam
Technically speaking, these associations only reveal which proteins are the most ‘popular’ in a disease, but do not directly assess the strength of evidence in each study and whether it relates to bona fide biological significance. However, the logic behind literature analysis often assumes the ‘wisdom of the crowd’ – with researchers acting as rational agents that invest their time and resources judiciously, and over time the research community should collectively expend most efforts toward truly significant proteins. Benchmarking the popularity lists against orthogonally curated annotations (e.g. GO or GWAS targets) suggests that they do often accurately predict functional significance. Recent developments further improve upon the quality of results by adjusting for the year and impact factor of associated publications [6,8] or by integrating text-mining and gene co-expression data to predict additional proteins that might be associated with a query term [5].
Deviant Workplace Behavior as Emotional Action: Discriminant and Interactive Roles for Work-Related Emotional Intelligence
Published in Human Performance, 2019
Michael D. Robinson, Michelle R. Persich, Cassandra Stawicki, Sukumarakurup Krishnakumar
The NEAT’s original scoring system used a norm-based (empirical: Corstjens et al., 2017) scoring key, which can capture the “wisdom of the crowd” (Legree, Psotka, Tremble, & Bourne, 2005). Subsequently, however, it was deemed better to obtain expert norms. This approach to keying has been termed rational (Corstjens et al., 2017) or expert (Bergman, Drasgow, Donovan, Henning, & Juraska, 2006) in the SJT literature. Experts originally consisted of 30 MBA students with an average of 8.15 years of work experience and an average age of 30. Now, however, experts consist of an even better sample – 82 student-nominated leaders with an average age of 40.85 and an average of 18.53 years of work experience. Experts hold leadership positions within a variety of fields such as law, health care, manufacturing, engineering, and service and they manage an average of 27.15 employees. Analyses revealed that expert and MBA norms are highly correlated, but expert norms can be favored for multiple reasons, including sample size, diversity of work experience, and longer tenure (Legree et al., 2005).
Discourses of professionalism: Metaphors, theory and practice
Published in Medical Teacher, 2019
Matthew Jon Links, Tim Wilkinson, Craig Campbell
Thus a student might behave professionally, but be racist. In both classifications meaning is constructed through interpersonal interactions. The key recommendations for an interpersonal discourse can be summarized as a focus on behaviors in practice, an acknowledgement of context and environment in making judgements, and the reliance on the “wisdom of the crowd”. These fit within Habermas understanding of a communicative frame with a focus on hermeneutics, collegial judgement, and creating conditions for an ideal exchange of views. The metaphor is the conversation. This frame is demonstrated by the discourse around judgement of professionalism in programmatic assessment which exemplifies the above principles (van der Vleuten et al. 2012). In a program of assessment, professionalism is a judgement, which requires interpretation and is based on observations and data, but is resolved through the wisdom of a community of experts.