Conferences on Reproducibility and Replicability in Economics and the Social Sciences (CRRESS)
Conferences on Reproducibility and Replicability in Economics and the Social Sciences (CRRESS)
批准号:
2217493
负责人:
Lars Vilhuber
金额:
$5.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-08-01 至 2024-07-31
中文摘要
该奖项为一系列关于社会科学可再生性、可复制性和透明度的虚拟和面对面会议提供部分支持。科学出版的目的是传播强有力的研究成果,将它们暴露在同行和其他感兴趣的各方的审查之下。科学文章应准确和完整地提供关于数据的来源和来源以及所使用的分析和计算方法的信息。然而,近年来,有人对科学文章及其附录中提供的信息的充分性表示怀疑。这被称为复制危机。会议将讨论以下主题:研究的启动、研究的进行、准备发表的研究以及发表后的审查。这些会议的产品将通过视频、演示材料和手稿向任何非与会者提供。本科生、研究生和职业研究人员将能够学习社会科学中透明、可重复和科学合理的研究的最佳实践。遵循各次会议讨论的最佳做法的研究将更具可验证性,因此更可信。对于希望实施循证决策的决策者和希望了解此类政策基础的公众来说,这些素质尤其重要。在整个研究过程中、在同行审查期间以及在结果传播之后,科学实践都相互作用,使人们能够讨论科学主张的真实性。调查人员将组织一系列会议,讨论减缓最佳做法采用的教育和程序障碍,期刊是否应该成为可重复性的验证者,是否(以及如何)使科学家的工作在研究过程的每个阶段都可重现,及其对资金、技术基础设施和本科生和研究生培训的影响。为该系列选择的主题通常不是纪律研讨会或会议的一部分,将第一次在这里向更广泛的受众介绍。大多数会议将以虚拟方式(在线)举行,但其他会议将与专业会议在同一地点或作为完整会议提交。会议结束后永久文物(演示文稿、录音、手稿)的可获得性将使其成为具有持续影响的资源。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This award provides partial support for a series of virtual and in-person conferences on the topics of reproducibility, replicability, and transparency in the social sciences. The purpose of scientific publishing is the dissemination of robust research findings, exposing them to the scrutiny of peers and other interested parties. Scientific articles should accurately and completely provide information on the origin and provenance of data and on the analytical and computational methods used. Yet in recent years, doubts about the adequacy of the information provided in scientific articles and their addenda have been voiced. This has been called the replication crisis. The conferences will address the following topics: the initiation of research, the conduct of research, the preparation of research for publication, and the scrutiny after publication. The products of these meetings will be available to any non-participant through videos, presentations materials, and manuscripts. Undergraduates, graduate students, and career researchers will be able to learn about best practices for transparent, reproducible, and scientifically sound research in the social sciences. Research that follows the best practices discussed in the various meetings will be more verifiable, and thus more credible. These qualities are especially important for policy makers that wish to implement evidence-based policymaking, and a public that wishes to understand the foundations of such policies.Scientific practices throughout the conduct of the research, during peer review, and after the dissemination of results all interact to enable a discourse about the veracity of scientific claims. The investigators will organize a sequence of conferences discussing educational and procedural barriers slowing down adoption of best practices, whether journals should be the verifiers of reproducibility, whether (and how) scientists' work can be made to be reproducible at every stage of the research process, and implications thereof for funding, technical infrastructure, and the training of undergraduate and graduate students. The topics chosen for the series are not usually part of disciplinary seminars or conferences and will be brought to a broader audience here for the first time. Most sessions will be held virtually (online), but others will be co-located with or submitted as complete sessions to professional meetings. The availability of permanent artifacts (presentations, recordings, manuscripts) after the conferences will allow this to be a resource with persistent impacts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
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DOI:
10.1162/99608f92.c2835391
发表时间:
2023
期刊:
Harvard Data Science Review
影响因子:
--
作者:
[Mendez-Carbajo, Diego, Dellachiesa, Alejandro]
通讯作者:
Dellachiesa, Alejandro
Reproducibility in Economics: Status and Update
经济学的可重复性:现状和更新
DOI:
10.1162/99608f92.80a1b88b
发表时间:
2023
期刊:
Harvard Data Science Review
影响因子:
--
作者:
[Hoynes, Hilary]
通讯作者:
Hoynes, Hilary
DOI:
10.1162/99608f92.9ba2bd43
发表时间:
2023
期刊:
Harvard Data Science Review
影响因子:
--
作者:
[Vilhuber, Lars, Schmutte, Ian, Michuda, Aleksandr, Connolly, Marie]
通讯作者:
Connolly, Marie
“Yes We Can!”: A Practical Approach to Teaching Reproducibility to Undergraduates
“是的,我们可以!”:向本科生教授再现性的实用方法
DOI:
10.1162/99608f92.9e002f7b
发表时间:
2023
期刊:
Harvard Data Science Review
影响因子:
--
作者:
[Ball, Richard]
通讯作者:
Ball, Richard
DOI:
10.1162/99608f92.db2a2554
发表时间:
2023
期刊:
Harvard Data Science Review
影响因子:
--
作者:
[Salmon, Timothy C.]
通讯作者:
Salmon, Timothy C.
共 9 条
Collaborative Research: Elements: TRAnsparency CErtified (TRACE): Trusting Computational Research Without Repeating It
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批准号:2209629
-
项目类别:Standard Grant
-
资助金额:$15.0万
-
财政年份:2022
-
负责人:Lars Vilhuber
-
依托单位:
RCN: Coordination of the NSF-Census Research Network
-
批准号:1507241
-
项目类别:Standard Grant
-
资助金额:$46.29万
-
财政年份:2014
-
负责人:Lars Vilhuber
-
依托单位:
RCN: Coordination of the NSF-Census Research Network
-
批准号:1237602
-
项目类别:Standard Grant
-
资助金额:$74.86万
-
财政年份:2012
-
负责人:Lars Vilhuber
-
依托单位:
NCRN-MN: Cornell Census-NSF Research Node: Integrated Research Support, Training and Data Documentation
-
批准号:1131848
-
项目类别:Standard Grant
-
资助金额:$299.96万
-
财政年份:2011
-
负责人:Lars Vilhuber
-
依托单位:
Synthetic Data User Testing and Dissemination
-
批准号:1042181
-
项目类别:Standard Grant
-
资助金额:$19.37万
-
财政年份:2010
-
负责人:Lars Vilhuber
-
依托单位:
Social Science Gateway to TeraGrid
-
批准号:0922005
-
项目类别:Standard Grant
-
资助金额:$39.35万
-
财政年份:2009
-
负责人:Lars Vilhuber
-
依托单位:
The economics of mass layoffs: displaced workers, displacing firms,and causes and consequences
-
批准号:0820349
-
项目类别:Continuing Grant
-
资助金额:$24.6万
-
财政年份:2008
-
负责人:Lars Vilhuber
-
依托单位:
海外基金