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Standard: Promoting Ethics in STEM with Transparency Initiatives that Work: An Interdisciplinary Investigation

标准：通过有效的透明度倡议促进 STEM 道德：跨学科调查

基本信息

批准号：
1926043
负责人：
Silvia Saccardo
金额：
$ 38.43万
依托单位：
Carnegie-Mellon University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1926043&HistoricalAwards=false
关键词：
Standard Promoting Ethics STEM Transparency

项目摘要

The production of valid scientific findings in STEM fields depends crucially on the ethical practices of scientists. Research integrity is receiving increased attention because of recent instances of data-fabrication, growing complaints about failure to replicate published results, and studies showing that researchers admit to engaging in questionable practices that undermine the validity of scientific results. To promote ethical practices, many universities and research institutions encourage researchers to be more transparent in the research process. Transparency initiatives include encouraging researchers to pre-register their studies - that is, to submit a study plan prior to beginning the research - or provide public proof of compliance with ethical standards. Little is known about how well such transparency initiatives work in terms of preventing questionable research practices. The current project explores when transparency policies work, when they may backfire, actually encouraging unethical behavior, and how to improve their design to make them more effective. It is crucial to investigate how initiatives designed to promote integrity interact with human behavior and to understand the contexts that cause people to bend rules while still thinking of themselves as honest. The current interdisciplinary project combines insights from psychology, behavioral economics, and machine learning to advance an understanding of how policies designed to promote transparency in research affect individuals' propensity to commit violations of ethical conduct. This project uses a unique combination of machine learning analysis of real-world data, survey data, and online experiments to explore the predictors and causes of unethical scientific conduct. One study examines pre-registered research plans from a large public database of clinical studies. Selected research plans are matched to the academic journal articles that resulted from the pre-registered studies, and articles that are retracted - withdrawn from the journal because of scientific problems with the work - are noted. The pre-registrations of publications that were vs. were not retracted are compared using computational methods at the intersection of natural language processing and machine learning. The goal of this analysis is to identify features of a pre-registered study plan (for example, being shorter or using more vague language) that predict that the resulting article will later be retracted. This analysis identifies when a well-intentioned intervention (pre-registration) fails to promote responsible research conduct. Another study surveys STEM researchers about causes of scientific misconduct and perceptions of transparency initiatives aimed at preventing it. This work is complemented by online experiments aimed at investigating the psychology of misconduct in a task where individuals have incentives to misreport information for private gains, which is analogous to the incentives scientists experience to tease significant results out of their data. These experiments investigate the conditions under which transparency policies that encourage individuals to provide evidence of ethical conduct might have unintended effects, increasing rather than decreasing individuals' tendency to violate ethical standards. A final set of experiments tests behavioral interventions that directly address the psychological drivers of misconduct identified in the previous studies. Taken together, this interdisciplinary project informs the design of transparency initiatives that work in promoting ethical conduct in STEM.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.

STEM领域有效科学发现的产生在很大程度上取决于科学家的道德实践。由于最近发生的数据造假事件、对未能复制已发表结果的投诉越来越多，以及研究人员承认从事了破坏科学结果有效性的可疑做法，研究诚信正受到越来越多的关注。为了促进道德实践，许多大学和研究机构鼓励研究人员在研究过程中更加透明。透明度倡议包括鼓励研究人员预先登记他们的研究--即在开始研究之前提交研究计划--或提供遵守道德标准的公开证据。关于这种透明度倡议在防止有问题的研究做法方面的效果如何，人们知之甚少。目前的项目探索了透明度政策何时奏效，何时可能适得其反，实际上鼓励了不道德的行为，以及如何改进其设计以使其更有效。调查旨在促进诚信的倡议如何与人类行为相互作用，并了解导致人们在仍然认为自己是诚实的情况下违反规则的背景，这一点至关重要。目前的跨学科项目结合了心理学、行为经济学和机器学习的见解，以促进对旨在促进研究透明度的政策如何影响个人违反道德行为的倾向的理解。该项目使用机器学习对真实世界数据的分析、调查数据和在线实验的独特组合，来探索不道德科学行为的预测因素和原因。其中一项研究从临床研究的大型公共数据库中检查了预先注册的研究计划。选定的研究计划与预先注册的研究产生的学术期刊论文相匹配，并注意到因工作中的科学问题而被撤回的论文。在自然语言处理和机器学习的交叉点上，使用计算方法比较了被撤回和未被撤回的出版物的预注册。这项分析的目的是确定预先登记的研究计划的特征(例如，较短或使用更模糊的语言)，这些特征预测结果文章稍后将被撤回。这一分析确定了善意的干预(注册前)何时未能促进负责任的研究行为。另一项研究调查了STEM研究人员关于科学不端行为的原因以及人们对旨在防止这种行为的透明度倡议的看法。这项工作还得到了在线实验的补充，这些实验旨在调查一项任务中不当行为的心理，在这项任务中，个人有动机为了私人利益而虚报信息，这类似于科学家从他们的数据中梳理重大结果的动机。这些实验调查了鼓励个人提供道德行为证据的透明度政策可能产生意想不到的影响的情况，增加了而不是减少了个人违反道德标准的倾向。最后一组实验测试了行为干预，这些干预直接解决了先前研究中确定的不当行为的心理驱动因素。总而言之，这个跨学科的项目为促进STEM道德行为的透明度倡议的设计提供了信息。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。