Bodily Encounter, Bearing Witness and the Engaged Activism of the Global Save Movement
Bibliographic record
Abstract
The global Save Movement, alongside other animal rights organisations and practices, has since 2010 sought to bring the experiences of nonhuman farmed animals into the public domain from privatized, usually hidden spaces of industrial procedure and slaughter. One key mechanism used is to conduct vigils held outside slaughterhouses, where activists gather to bear witness to the passing of nonhuman animals in trucks, and to raise awareness of the suffering of animals to passers-by. Central to the practice are the roles played by emotional engagement and bodily encounter with the nonhuman animals; the movement is founded on a self-styled ‘love-based’ compassion for other living beings. In 2014, I joined the Save Movement in Toronto for a number of vigils, engaging in an autoethnographic study of the means by which activists employ emotional labour, bearing witness and bodily encounter in foregrounding the realities of life for industrially farmed nonhuman animals. This article argues that the Save Movement represents a new moment (although not wholly without precedent) in the practices of animal rights activism. Working from the intellectual standpoint of Critical Animal Studies, the structure of the paper employs this autoethnographic and emotionally-affected personal account of taking part as a researcher-activist in the vigils, to offer access to experiences of how emotion, activism and empathy overlap in ‘coming to care’ for nonhuman others in public settings. The article seeks to elucidate the Save Movement’s emphasis on bodily encounter and the making visible of already existing embodied entanglements with farmed nonhuman animals, and suggests this form of engaged witnessing offers opportunity for radically reimagining our species’ existing relationships with those species we currently identity as food.
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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 | 0.003 | 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 | 0.003 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".