Biopower, Biopolitics, Biosemiotics: Entangling Mortalities and Moralities
Bibliographic record
Abstract
While biosemiotics moves in the direction of liberating both biology and semiotics from strict observance of the paradigms of the 19th and 20th centuries – via evo-devo-eco models and the ontological turn – we propose a glance backwards as well as a sharper focus on the social and sexual conditions of the present and foreseeable future. We bring together contemporary discourses on feminism, biophilia, biophobia, essentialisms, and denial, with the prescient ideas of biopower developed by Michel Foucault with respect to the nation-state. He addressed a bevy of pathologies endemic in the societies he witnessed at that time; these conditions persist and indeed have flourished, ranging from sexism, to racism, to classism, to technologism, to the outsourcing of work and the exporting of refuse, to the addictive mantra of “sustainability”, all culminating in society’s exercising of power over both life and death, both living and dying, both near and far. We also find biopower a suitable critical lens for pursuing the pathologies surrounding population – population as generated, as regulated, as ignored, as denied, whether or not acknowledged as being the work of wombs.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.096 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".