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EAGER: Accelerating the Pace of Discovery by Changing the Peer Review Algorithm

EAGER: Accelerating the Pace of Discovery by Changing the Peer Review Algorithm
EAGER:通过改变同行评审算法加快发现步伐
批准号:
1042164
负责人:
Stefano Allesina
金额:
$24.01万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-08-01 至 2014-07-31

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中文摘要
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英文摘要
Peer review is the main tool for scrutinizing scholarly publications, grant proposals and career advancements in science. However, the current peer review system is under severe strain, with consequences for the quality of science and the rapidity of dissemination of scientific results. Several studies have found that the current way of performing peer review can be inefficient, slow, and even biased. Almost every scientist has ideas on how to improve the system, but it is very difficult, if not impossible, to perform experiments to determine which measures are most effective. The project implements a simulation framework in which many ideas of how to improve the review process can be quantitatively tested.Intellectual Merit The framework is built using agent-based modeling. Scientists, manuscripts and journals are digital agents and a peer review system emerges from their interaction. Multiple experiments can be run: for example, one proof-of-concept application shows how changing the way peer review is performed can dramatically alter the pace at which science is disseminated.The research develops a full-fledged and open-source simulation software that allows to study alternatives to the current system.Broader Impacts The proposed work is potentially transformative of the way science is carried out. This framework can be used to identify better and more efficient models for peer review, leading to profound changes on scientific publishing and funding. Also, if this exploratory research is successful, a new computational branch of sociology of science could emerge. Changing the way peer review is performed to favor faster and more efficient solutions could potentially have broad effects on the daily work of scientists, including more time for academic training and research, and less time spent revising and reformatting manuscripts and grant proposals. Favoring unbiased practices could enlarge the representation of minorities in science.
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Revisiting the relationship between phylogenetic diversity and productivity
  • 批准号:
    2022742
  • 项目类别:
    Standard Grant
  • 资助金额:
    $44.93万
  • 财政年份:
    2020
  • 负责人:
    Stefano Allesina
  • 依托单位:
CAREER: Scientific Computing for a New Generation of Ecologists
  • 批准号:
    1148867
  • 项目类别:
    Standard Grant
  • 资助金额:
    $59.92万
  • 财政年份:
    2012
  • 负责人:
    Stefano Allesina
  • 依托单位:
海外基金