'Of place' or 'of people': exploring the animal spaces and beastly places of feral cats in southern Ontario
Bibliographic record
Abstract
Feral cats are contentious and transgressive, with opposing views on whether to classify them as abandoned pets, wild animals, or invasive species. Concerns about their welfare often conflict with fears that they are impacting native fauna. This paper presents the results of a case study of human–feral cat relations that took place in southern Ontario, Canada in 2014. This research investigates the discursive constructions of feral cats and their 'animal spaces' using the results of 40 semi-structured interviews. Following recent calls to move beyond human representations of animals and better integrate animals' geographies, this study also explores the 'beastly places' of feral cats using the results of field observations of 20 feral cat colonies and anecdotal evidence from colony caretakers. The results emphasize the diversity of free-living contexts and the complexity of management options. This paper ends by discussing the place-making practices of cats, along with their potential ethical ramifications. Overall, it illustrates the importance of spatial factors in understanding the complex social and ethical dynamics of human–animal relations, and advances an understanding of nonhuman animals as inhabitants of personally meaningful homes.This is an Accepted Manuscript of an article published by Taylor & Francis in Social & Cultural Geography on 2017-01-04, available online: https://www.tandfonline.com/10.1080/14649365.2016.1275754. Deposited by shareyourpaper.org and openaccessbutton.org. We've taken reasonable steps to ensure this content doesn't violate copyright. However, if you think it does you can request a takedown by emailing help@openaccessbutton.org.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".