Animals, Affect and Annihilation: Campaigns against Canids in Postwar Canada
Bibliographic record
Abstract
Abstract This essay suggests that culling campaigns against canids in postwar Canada have striking affective dimensions. Drawing on examples of canid management in the 1950s and 60s from Nunavik, Alberta, and Ontario, we contend that the killing of supposedly rabid dogs and wild canids was predominantly about affective excess and emotional management. The wildness of these animals was perceived to lead to excessive nonhuman affectivity, which was seemingly exacerbated by rabies. Human encounters with these animals were characterised by excessive affective responses, a result of long-standing fears of rabies, anxieties about northernness and assertions of ‘civilisation’ in the context of settler colonialism. This fear was then channelled into round ups and killings of canids. The killing was what Monique Scheer calls an ‘emotional practice’ designed to soothe anxieties, to cleanse and to civilise. Drawing on archival and other documentary sources, we aim to show the value in exploring more fully the intersections between affect and animal histories.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".