Standards of conduct and reporting in evidence syntheses that could inform environmental policy and management decisions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Accurate, unbiased and concise synthesis of available evidence following clear methodology and transparent reporting is necessary to support effective environmental policy and management decisions. Without this, less reliable and/or less objective reviews of evidence could inform decision making, leading to ineffective, resource wasteful interventions with potential for unintended consequences. We evaluated the reliability of over 1000 evidence syntheses (reviews and overviews) published between 2018 and 2020 that provide evidence on the impacts of human activities or effectiveness of interventions relevant to environmental management. The syntheses are drawn from the Collaboration for Environmental Evidence Database of Evidence Reviews (CEEDER), an online, freely available evidence service for evidence users that assesses the reliability of evidence syntheses using a series of published criteria. We found that the majority of syntheses have problems with transparency, replicability and potential for bias. Overall, our results suggest that most recently published evidence syntheses are of low reliability to inform decision making. Reviews that followed guidance and reporting standards for evidence synthesis had improved assessment ratings, but there remains substantial variation in the standard of reviews amongst even these. Furthermore, the term 'systematic review', which implies conformity with a methodological standard, was frequently misused. A major objective of the CEEDER project is to improve the reliability of the global body of environmental evidence reviews. To this end we outline freely available online resources to help improve review conduct and reporting. We call on authors, editors and peer reviewers to use these resources to ensure more reliable syntheses in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 it