Decline effects are rare in ecology: a meta-meta-analysis
Bibliographic record
Abstract
The scientific evidence base on any given topic changes over time as more studies are published. Currently, there is widespread concern about non-random, directional changes over time in the scientific evidence base associated with many topics. In particular, if studies finding large effects (e.g., large differences between treatment and control means) tend to get published quickly, while small effect sizes tend to get published slowly, the net result will be a decrease over time in the estimated magnitude of the mean effect size, known as a "decline effect". If decline effects are common, then the published scientific literature will provide a biased and misleading guide to management decisions, and to the allocation of future research effort. We compiled data from 466 meta-analyses in ecology to look for evidence of decline effects. We found that decline effects are rare. Only ~5% of ecological meta-analyses truly exhibit a directional change in mean effect size over time arising for some reason other than random chance, usually but not always in the direction of decline. Most apparent directional changes in mean effect size over time are attributable to regression to the mean, consistent with primary studies being published in random order with respect to the effect sizes they report. Our results are good news: decline effects are the exception to the rule in ecology. Identifying and rectifying rare cases of true decline effects remains an important task, but ecologists should not overgeneralize from anecdotal reports of decline effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.439 | 0.002 |
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, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".