Predict science to improve science
Abstrak
Systematic collection of predictions of research findings can provide many benefits Many fields of research, such as economics, psychology, political science, and medicine, have seen growing interest in new research designs to improve the rigor and credibility of research (e.g., natural experiments, lab experiments, and randomized controlled trials). Interest has similarly grown in efforts to increase transparency, such as preregistration of hypotheses and methods, that seek to allay concerns that improved research designs do not address per se, such as publication bias and p-hacking. Yet, although these efforts improve the informativeness and interpretation of research results, relatively little attention has been paid to another practice that could help to achieve this goal: relating research findings to the views of the scientific community, policy-makers, and the general public. We suggest below three broad ways in which systematic collection of predictions of research results will prove useful: by improving the interpretation of research results, mitigating bias against null results, and improving predictive accuracy and experimental design.
Topik & Kata Kunci
Penulis (3)
Stefano DellaVigna
Devin G. Pope
Eva Vivalt
Akses Cepat
- Tahun Terbit
- 2019
- Bahasa
- en
- Total Sitasi
- 92×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1126/science.aaz1704
- Akses
- Open Access ✓