Integration and specialism: complementary not contradictory
Bibliographic record
Abstract
Psychiatry, behavioural disturbance and risk management have conceptually coexisted for hundreds of years, however, prior to the 1800 Criminal Lunatics Act, drafted exigently following an attempt on the life of the then King by the “insane” Hadfield, the only means of care was custodial, under arcane vagrancy legislation, such as the 1714 Vagrancy Act, or on the basis of the poor laws. Mentally disordered individuals were either incarcerated as criminals or paupers (Select Committee, 1807) falling under the responsibility of local parish councils. At this point, incarceration was just that, with prisons hosting most detained mentally disordered individuals, under the indefinite see of the monarch. The first vision for caring, secure, environments for mentally disordered individuals was in the development of asylums following the 1808 County Asylums Act, which recognised that detaining, “lunatics and other insane persons…in Gaols, Houses of Correction, Poor Houses and Houses of Industry, is highly dangerous and inconvenient.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.042 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".