Devoutman:
'''James Allen Evans''' is a [[University of Chicago]] [[sociologist]], currently serving as director of the Computational Social Science Program and the Knowledge Lab, and senior fellow at the Computation Institute. His work uses [[large-scale data]] and [[machine learning]] to explore such phenomena as the [[emergence of ideas]], shared [[patterns of reasoning]], attention, communication and certainty.<ref>https://ift.tt/2z4wCnV>
==Early life and education==
Evans obtained a B.A. in [[Anthropology]] from [[Brigham Young University]], and an M.A. in Sociology from [[Stanford University]]. He co-founded and served as executive director of the [[Utah High School for the Performing and Fine Arts]] and edited the ''[[American Journal of Sociology]]''.
==Research==
Much of Evans's research relates to the effect of computers on science. He is skeptical of [[data-driven science]] proponents' view that in the future, [[hypotheses]] will become obsolete as new knowledge simply emerge from mechanical application of algorithms that [[data mining|mine data]] for plausible patterns. Rather, in 2010, he made the prediction that "within a decade, even more powerful tools will enable automated, high-volume [[hypothesis generation]] to guide high-throughput experiments in [[biomedicine]], [[chemistry]], [[physics]], and even the [[social sciences]]".<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref><ref>https://ift.tt/3fSWeom>
Evabs has studied industrial partnerships with scientists and concluded that while they contribute to the limited funds and materials dedicated to academic research, they also make science less novel and influence scientists to be less persistent in their inquiry. He also participated in a research team that analyzed more than 200,000 [[Wikipedia]] pages<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref> and found that "Wikipedia teams comprised by a balance of politically polarized individuals perform better than groups comprised of political partisans and even moderates. . . . Platforms that discourage all user bias may thus be inefficient or unsustainable."<ref></ref>
Evans is a frequent collaborator with [[Jacob G. Foster]], and has researched with him topics such as [[cultural evolution]] with [[multiple inheritance]]<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref> and dynamic [[network model]]s of science's unfolding structure.<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref> Respectively, they drew distinctions between vertical transmission and horizontal transfer, and concluded that adding more node types to network models of science and other creative domains would likely lead to a superlinear increase in prediction and understanding.
Evans has studied what factors make a scientist's work more influential. For example, he found a strong [[first-mover]] advantage in which "an early mediocre article on a topic will often receive more citations than a later excellent one". While he cautioned that focusing overmuch on the momentum of an article's reception could cause scientists and funders to "prematurely abort ideas that may yet have a second or third act to play", he noted that by exposing common assumptions and practices of science to scrutiny and explicit evaluation, citation prediction could also be a path to creating algorithmic [[roboscientist]]s that would be more creative, risky, persistent, and wide-reading than human scientists.<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref>
==References==
[[Category:American sociologists]]
[[Category:University of Chicago faculty]]
[[Category:Brigham Young University alumni]]
[[Category:Stanford University alumni]]
[[Category:Living people]]
==Early life and education==
Evans obtained a B.A. in [[Anthropology]] from [[Brigham Young University]], and an M.A. in Sociology from [[Stanford University]]. He co-founded and served as executive director of the [[Utah High School for the Performing and Fine Arts]] and edited the ''[[American Journal of Sociology]]''.
==Research==
Much of Evans's research relates to the effect of computers on science. He is skeptical of [[data-driven science]] proponents' view that in the future, [[hypotheses]] will become obsolete as new knowledge simply emerge from mechanical application of algorithms that [[data mining|mine data]] for plausible patterns. Rather, in 2010, he made the prediction that "within a decade, even more powerful tools will enable automated, high-volume [[hypothesis generation]] to guide high-throughput experiments in [[biomedicine]], [[chemistry]], [[physics]], and even the [[social sciences]]".<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref><ref>https://ift.tt/3fSWeom>
Evabs has studied industrial partnerships with scientists and concluded that while they contribute to the limited funds and materials dedicated to academic research, they also make science less novel and influence scientists to be less persistent in their inquiry. He also participated in a research team that analyzed more than 200,000 [[Wikipedia]] pages<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref> and found that "Wikipedia teams comprised by a balance of politically polarized individuals perform better than groups comprised of political partisans and even moderates. . . . Platforms that discourage all user bias may thus be inefficient or unsustainable."<ref></ref>
Evans is a frequent collaborator with [[Jacob G. Foster]], and has researched with him topics such as [[cultural evolution]] with [[multiple inheritance]]<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref> and dynamic [[network model]]s of science's unfolding structure.<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref> Respectively, they drew distinctions between vertical transmission and horizontal transfer, and concluded that adding more node types to network models of science and other creative domains would likely lead to a superlinear increase in prediction and understanding.
Evans has studied what factors make a scientist's work more influential. For example, he found a strong [[first-mover]] advantage in which "an early mediocre article on a topic will often receive more citations than a later excellent one". While he cautioned that focusing overmuch on the momentum of an article's reception could cause scientists and funders to "prematurely abort ideas that may yet have a second or third act to play", he noted that by exposing common assumptions and practices of science to scrutiny and explicit evaluation, citation prediction could also be a path to creating algorithmic [[roboscientist]]s that would be more creative, risky, persistent, and wide-reading than human scientists.<ref>Liquid error: wrong number of arguments (given 1, expected 2)</ref>
==References==
[[Category:American sociologists]]
[[Category:University of Chicago faculty]]
[[Category:Brigham Young University alumni]]
[[Category:Stanford University alumni]]
[[Category:Living people]]
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