Bibliographic record
Abstract
‘Terrier work’ is an historical and deeply significant rural practice in the United Kingdom, in which small or medium size terriers are employed to track, capture and kill foxes in the larger context of an organized foxhunt. Between 2007-2009, I spent time following a small group of ‘terrier men’ and their dogs around the East Midlands countryside as part of an ethnographic project on the use of dogs in rural (mainly fox) hunting cultures. A small faction of these terrier men living in England and Wales participate in a quasi-legal hunting subculture. In this paper, and drawing heavily upon animal standpoint theory (Best, 2013), I shift analytic focus in human-nonhuman animal studies away from human constructions/ uses/ meanings of animals in animal ‘blood sports’ (Gillett & Gilbert, 2013), and consider a fox hunting case study from the positions and subjectivities of the animals involved. This reading calls sociologists of sport and physical culture to reconsider how human-animal sports, analyzed from marginalized or silenced standpoints, direct attention to the interplay between power, instincts, and desires involved when species interactively meet.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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".