Principles for the production of evidence‐based guidance for conservation actions
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
Abstract Many types of guidance documents inform conservation by providing practical recommendations for the management of species and habitats. To ensure effective decisions are made, such guidance should be based upon relevant and up‐to‐date evidence. We reviewed conservation guidance for mitigation and management of species and habitats in the United Kingdom and Ireland, identifying 301 examples produced by over 50 organizations. Of these, only 29% provided a reference list, of which only 32% provided reference(s) relevant to justify the recommended actions (9% of the total). Furthermore, even this guidance was often outdated, lacked a methodology for production, or did not highlight uncertainty in the key evidence that supported the recommendations. These deficiencies can lead to misguided and ineffective conservation practices, policies, and decisions, and a waste of resources. Based on this review and co‐design by experts from 14 organizations, we present a set of principles for ensuring sufficient and relevant evidence is transparently incorporated into future conservation guidance. Producing evidence‐based guidance in line with these principles would enable more effective conservation outcomes.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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