Established frameworks to understand problems with reproducibility in science begin with the relationship between our understanding of the prior probability of a claim and the statistical certainty that should be demanded of it, and explore the ways in which independent investigations, biases in study design and publication bias interact with these considerations. We propose a complementary perspective; namely, that to improve reproducibility in science, our interpretation of the persuasiveness of evidence (e.g., statistical significance thresholds) should be responsive to our understanding of the effort that would be required to improve that evidence. We will quantify this notion in some formal settings. Indeed, we will demonstrate that even simplistic models of evidence publication can exhibit an improvable evidence paradox, where the publication of easily improvable evidence in favor of a claim can best seen as evidence the claim is false.

中文翻译：

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易于改进的证据的矛盾性质

理解科学中可重复性问题的既定框架始于我们对索赔先验概率的理解与应要求的统计确定性之间的关系，并探索独立调查、研究设计中的偏见和发表偏见的方式与这些考虑因素相互作用。我们提出了一个互补的观点；也就是说，为了提高科学的可重复性，我们对证据说服力的解释（例如，统计显着性阈值）应该响应我们对改进证据所需努力的理解。我们将在一些正式的环境中量化这个概念。事实上，我们将证明，即使是简单的证据发布模型也可以表现出可改进的证据悖论，