Peer Review #3 of "Access to scientific literature by the conservation community (v0.1)"
Bibliographic record
Abstract
Access to the scientific literature is perceived to be a challenge to the biodiversity conservation community, but actual level of literature access relative to needs has never been assessed globally.We examined this question by surveying the constituency of the International Union for Conservation of Nature (IUCN) as a proxy for the conservation community, generating 2,285 responses.Of these respondents, ~97% need to use the scientific literature in order to support their IUCN-related conservation work, with ~50% needing to do so at least once per week.The crux of the survey revolved around the question, "How easy is it for you currently to obtain the scientific literature you need to carry out your IUCN-related work?" and revealed that roughly half (49%) of the respondents find it not easy or not at all easy to access scientific literature.We fitted a binary logistic regression model to explore factors predicting ease of literature access.Whether the respondent had institutional literature access (55% do) is the strongest predictor, with region (Western Europe, the United States, Canada, Australia and New Zealand) and gender (male) also significant predictors.Approximately 60% of respondents from Western Europe, the United States, Canada, Australia and New Zealand have institutional access compared to ~50% in Asia and Latin America, and ~40% in Eastern Europe and in Africa.Nevertheless, accessing free online material is a popular means of accessing literature for both those with and without institutional access.The four journals most frequently mentioned when asked which journal access would deliver the greatest improvements to the respondent's IUCN-related work were Conservation Biology, Biological Conservation, Nature, and Science.The majority prefer to read journal articles on screen but prefer to read books in hard copy.Overall, it is apparent that access to the literature is a challenge facing roughly half of the conservation community worldwide.
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How this classification was reachedexpand
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 | 0.031 | 0.190 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.562 | 0.418 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".