复制的可靠性:对计算复制的研究
Nate Breznau1, Eike Mark Rinke2, Alexander Wuttke3
1Organization and Program Planning, German Institute for Adult Education-Leibniz Center of Lifelong Learning, Bonn 53175, Germany.
Royal Society open science
|March 20, 2025
概括
计算复制成功因透明度而有所不同. 对原始数据和代码的透明访问改善了结果验证,强调了需要更好的研究实践和培训,以确保科学可重复性.
科学领域:
- 计算社会科学 计算社会科学
- 研究方法研究方法论.
背景情况:
- 可复制性对于科学完整性至关重要.
- 计算复制,或用代码复制分析,面临着挑战.
- 研究人员方法的变化可能会影响复制成功.
研究的目的:
- 为了研究研究人员在计算复制中的变性.
- 为了比较透明和不透明条件之间的繁殖成功率.
- 在计算复制工作流程中识别错误的原因.
主要方法:
- 85个独立团队试图数量复制一项关于政策偏好和移民的原始研究.
- 团队被分为"透明" (接收的代码和数据) 和"不透明" (只接收方法和结果) 组.
- 对工作流进行了定性分析,以确定错误来源.
主要成果:
- 与不透明组 (89.3%) 相比,透明组在验证原始结果方面取得了更高的成功率 (95.7%).
- 精确的数值复制到小数点二是不太常见的,特别是在不透明的组 (48.1%).
- 错误和程序变化被确定为错误的主要原因,透明度有助于可靠的成功.
结论:
- 透明度,包括对原始代码和数据的访问,对于可靠的计算复制至关重要.
- 需要提高培训,机构检查,以及对研究复杂性的更大认识.
- 减少在复制任务中的主观困难可以提高研究人员的参与度和成功.
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