Bibliographic record
Abstract
The article is organized as follows. Part H traces the conceptual shift in legal theory from thinking about the juridical subject as a bearer of rights to a bearer of interests. This provides the necessary context for my reframing the bearer of interests as a bearer of desires. Part III begins to explore the implications of this move, drawing on what I call the "ethic of positivity" in parts of queer theory that celebrates the potential for sexual desires to transcend identity categories. This theory suggests that the ethical promise of settlement derives from the potential of the subject's interests to reach outside the bounds of liberal legalism and articulate a field of justice that is more substantive, pleasurable, and new. Part IV pushes this claim to its limit by underscoring the fact that some people report their lived experiences of sexuality as unwanted and therefore potentially harmful. This suggests that the ethical promise of settlement derives from a collaborative process that respects the other's autonomy, what I call the "ethic of mutuality" in parts of queer theory. Finally, the article concludes by suggesting that these two ethics come together, necessarily albeit problematically, in the legal doctrine of consent. One of our tasks ahead should be to continue refining the legal doctrine so that it strikes an appropriate balance between these ethical imperatives in law. Throughout the article, I will illustrate these points by reference to a case study of two separating spouses negotiating the terms of their divorce, which should help to ground my contributions in a practical legal context.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.075 | 0.010 |
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".