Experiencing in History (20th century): Some Methodological Issues on Women Confinement
Bibliographic record
Abstract
The object of this paper is a theoretical/methodological/epistemological reflection on the possibility, for the researcher in history, to measure the experience of people which are the subject of social regulation measures, via confinement in closed institution. The paper draws both on archival sources and interdisciplinary theoretical works, which are put in relation constantly. In the first place, I will build on my own experience as an historian and different sources for analysis : sources from public closed institutions in Belgium (institutions for young offenders), judicial sources from Quebec (child magistrates in Montreal), hospital sources (private psychiatric institution for women in Belgium). Second, I integrate scientific literature from the historical, criminological, sociological and philosophical sciences, especially on the question of: discourse analysis and the need to link it with empirical research (contribution of the two types of analysis); individual experience in the judiciary and the possibility to measure it ; the personal experience of the researcher, which necessarily affects his understanding of individual experience he studies; gender distinctions (work on male or female detainees, contribution of feminist historiography) influencing the methodologies. The authors mobilized will include: Gilles Chantraine, Claude Faugeron, Michel Foucault, Michel de Certeau, Erving Goffman, Mary Bosworth, Joan Sangster, Corinne Rostaing, Elsa Dorlin, Judith Butler, Joan Scott, François Dubet, Georg Simmel, Antoinette Chauvenet.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.014 | 0.041 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".