Bibliographic record
Abstract
Committed to the State Asylum examines the evolution of the asylum as the response to insanity in nineteenth-century Quebec and Ontario.Focusing on the creation and development of governmentfunded asylums for the insane -among the largest and most important nineteenth-century institutions in both provinces -James Moran argues that asylum development was the result of complex relationships among a wide array of people, including state inspectors and administrators, asylum doctors, local magistrates, jail surgeons, religious authorities, and the relatives and neighbours of those who were considered to be insane.Unlike other studies, Committed to the State Asylum shows the important role that the community played in shaping the asylum and tackles the thorny issue of state development, explaining how state asylums developed differently in each province.Moran considers Canada's pioneering institutional efforts at dealing with the criminally insane and why those efforts lasted only a short time, shedding new light on the debate about the nature and extent of state involvement in nineteenth-century Canadian society.Committed to the State Asylum offers new insights into the ways in which both ordinary families and the state understood and responded to those they thought had crossed the boundaries of sane behaviour.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.839 | 0.648 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".