Bibliographic record
Abstract
This essay considers Levinas' face-to-face ethical relation together with Gilles Deleuze and Felix Guattari's concept of ‘becoming animal’ as a response to the radical dehumanisation involved in biopolitics. Framing his analysis in terms of an archaic law banning wrongdoers as wolves, Giorgio Agamben shows that biopolitics strips humans of subjectivity and exposes them to political power. Levinas' answer to radical dehumanisation is an ethical humanism of the other, but his ethical program is barred from politics. Moreover, he writes that in his own experience of dehumanisation, the only ethical being he encountered was Bobby, the camp dog. It seems biopolitics calls for an ethical politics that we might possess as bare life, outside of the autonomous, individualising conditions of the humanist subject. To this aim, I apply Deleuze and Guattari's concept of becoming animal as a devise to transport Levinas' ethics of alterity to the political realm.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.042 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".