Bestiary of Questionable Research Practices in Psychology
Bibliographic record
Abstract
Questionable research practices (QRPs) pose a significant threat to the quality of scientific research. However, historically, they remain ill-defined, and a comprehensive list of QRPs is lacking. In this article, we address this concern by defining, collecting, and categorizing QRPs using a community-consensus method. Collaborators of the study agreed on the following definition: QRPs are ways of producing, maintaining, sharing, analyzing, or interpreting data that are likely to produce misleading conclusions, typically in the interest of the researcher. QRPs are not normally considered to include research practices that are prohibited or proscribed in the researcher’s field (e.g., fraud, research misconduct). Neither do they include random researcher error (e.g., accidental data loss). Drawing from both iterative discussions and existing literature, we collected, defined, and categorized 40 QRPs for quantitative research. We also considered attributes such as potential harms, detectability, clues, and preventive measures for each QRP. The results suggest that QRPs are pervasive and versatile and have the potential to undermine all stages of the scientific enterprise. This work contributes to the maintenance of research integrity, transparency, and reliability by raising awareness for and improving the understanding of QRPs in quantitative psychological research.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchResearch integrity Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | MetaresearchResearch integrity Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | medium |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.671 | 0.797 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.032 | 0.018 |
| Science and technology studies | 0.015 | 0.085 |
| Scholarly communication | 0.033 | 0.032 |
| Open science | 0.007 | 0.028 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".