The Insanities of Reproduction: Medico-legal Knowledge and the Development of Infanticide Law
Bibliographic record
Abstract
Drawing on autopoiesis theory, Ward (1999) challenges the established view that the adoption of the English infanticide law in 1922 (amended 1938) is an example of the medicalization of law, insisting that the 1922 Act embodied a lay biological theory and that contemporary psychiatric theories of the ‘insanities of reproduction’ focused on socio-economic, rather than biological, stressors. Both the medicalization and autopoiesis interpretations of infanticide law are misplaced. A broader review of the medical literature discussed by Ward, and of a related anthropological literature he does not treat, reveals a more complex picture: while Ward’s critique of the medicalization thesis is broadly apposite, and an associated anthropological literature was also more socio-economic than bio-racist (Reekie, 1998), there was a bio-medical strand of thought, as well as an equally biological atavistic line of theory regarding infanticide, which ran alongside the socio-economic model. In addition, the expressed biologism of infanticide law, whatever its origins, can still be thought of as contributing to the medicalization of law subsequent to its passage and amendment, especially given the dominance of the bio-medical model in psychiatry since the 1960s.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.054 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".