A practitioner’s perspective on what we know about safeguarding pollinators on farmland
Bibliographic record
Abstract
Farmers understand the general importance of pollinators, and through their management of cropped land and non-cropped areas on the farm they have the potential to do more than any other group to help provide habitat and food for pollinating insects. Pollinators are a continually topical issue for the media and policymakers, and against this challenging background it is not always clear what the best approaches are for farmers or land managers to take to protect and increase pollinators. What do we know about the state of pollinator populations on farmland in the UK? To what extent can the use of agri-environment measures, the maintenance and creation of other habitats, and the management of pesticide use, help protect and increase pollinator populations? This paper explores these questions by providing a farming perspective on the evidence in these areas; reflecting on what the knowns and unknowns are, and identifying where there are still gaps in the evidence that need to be plugged to better conserve and manage pollinators on farmland.
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.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".