Toxic politics: Acting in a permanently polluted world
Bibliographic record
Abstract
Toxicity has become a ubiquitous, if uneven, condition. Toxicity can allow us to focus on how forms of life and their constituent relations, from the scale of cells to that of ways of life, are enabled, constrained and extinguished within broader power systems. Toxicity both disrupts existing orders and ways of life at some scales, while simultaneously enabling and maintaining ways of life at other scales. The articles in this special issue on toxic politics examine power relations and actions that have the potential for an otherwise. Yet, rather than focus on a politics that depends on the capture of social power via publics, charismatic images, shared epistemologies and controversy, we look to forms of slow, intimate activism based in ethics rather than achievement. One of the goals of this introduction and its special issue is to move concepts of toxicity away from fetishized and evidentiary regimes premised on wayward molecules behaving badly, so that toxicity can be understood in terms of reproductions of power and justice. The second goal is to move politics in a diversity of directions that can texture and expand concepts of agency and action in a permanently polluted world.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.051 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".