Blurred boundaries: a double-voiced dialogue on regulatory regimes and embodied space
Bibliographic record
Abstract
In this paper, I take up de Certeau's invitation to attend to the spatial practices that 'secretly structure the determining conditions of social life' (1984: 97). I do so conscious of Moran's reminder that 'the corporeal is never far away from the spatial themes of law' (2003: 91), and Eisenstein's assertion that to become more specific 'is actually to encompass more of humanity'. (1994: 4). Practices of democracy (and practices of justice) presume and implicate very specific kinds of spaces and bodies. In attempting to re-imagine democracy, Eisenstein suggests that we focus on the body of the pregnant woman, a body that has been the object of extensive analysis and regulation. The shifting and blurred boundary between the woman and the life she carries is the subject of contestation (Fried 1990). The body of the woman is characterised by some as permeable, by others as inviolable. The foetus is sometimes conceptualised as part of the woman's body, at other times as merely enclosed within her body, and the discussion often turns to contests of rights between mother and foetus (Thomson 1986). Always marked by race, class, and ability, the pregnant body is sometimes celebrated, sometimes reviled (Solinger 1992).
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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 | 0.033 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.018 | 0.112 |
| Scholarly communication | 0.027 | 0.040 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.022 | 0.025 |
| 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".