Bibliographic record
Abstract
Contents: Introduction, Rob I. Mawby and Richard Yarwood Part I Rural Policing: Rural police: a comparative overview, Rob I. Mawby Policing rural Canada and the United States, Joseph F. Donnermeyer, Walter S. DeKeseredy and Molly Dragiewicz Policing the outback: impacts of isolation and integration in an Australian context, Elaine Barclay, John Scott and Joseph F. Donnermeyer Rural policing in France: the end of genuine community policing, Christian Mouhanna Plural policing in rural Britain, Rob I. Mawby Governing Crime in rural UK: risk and representation, Daniel Gilling Big Brother goes to the countryside: CCTV surveillance in rural towns, Craig Johnstone Whose Blue Line is it anyway? Community policing and partnership working in rural places, Richard Yarwood. Part II Policing the Rural: Policing rural protest, Michael Woods Still 'out of place in the country'? Travellers and the post-productivist rural, Keith Halfacree Gypsies and travellers in the countryside: managing a risky population, ZoA James A trip in the country? Policing drug use in rural settings, Adrian Barton, David Storey and Claire Palmer 'It's not all Heartbeat you know': policing domestic violence in rural areas, Greta Squire and Aisha Gill The thin green line? Police perceptions of the challenges of policing wildlife crime in Scotland, Nicholas R. Fyfe and Alison D. Reeves Policing poaching and protecting pachyderms: lessons learned from Africa's elephants, A.M. Lemieux Policing agricultural crime, Joseph F. Donnermeyer, Elaine M. Barclay and Daniel Mears Policing the producer: the bio-politics of farm production in New Zealand's productivist landscape, Matthew Henry W(h)ither rural policing? An afterword, Richard Yarwood and Rob I. Mawby Bibliography Index.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".