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Record W2994625798 · doi:10.7202/1065825ar

Politics, patronage and scandal at the Provincial Lunatic Asylum, 1848-1857

2019· article· en· W2994625798 on OpenAlexvenueaboutno aff
Joseph Dunlop

Bibliographic record

VenueOntario History · 2019
Typearticle
Languageen
FieldMedicine
TopicHistorical and Scientific Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLunaticFeudPoliticsLawPolitical science

Abstract

fetched live from OpenAlex

In the mid-nineteenth century, Canada West’s Provincial Lunatic Asylum sat at the heart of a system of patronage. It was this system of patronage that allowed the politician John Rolph to secure the position of Asylum Medical Superintendent for his protégé, Dr. Joseph Workman. However, this same period also witnessed the beginning of a shift away from patronage-based appointments towards a new style of civil service characterized by expertise rather than political or personal connections. Among those who supported this new ideal was the politician and journalist George Brown, who heavily criticized Workman’s appointment as an example of political patronage. Yet, the antagonism that continued to escalate between Brown and Workman owed its genesis not only to Brown’s ideals, but was also fueled by the considerations of party factionalism as well as by the clash of two strong personalities. Their feud would reach its climax in the heavily publicized 1857 libel suit, Workman v. Brown. Sharing a common devotion to the Reform party and to lunacy reform, an examination of the feud between Brown and Workman reveals the many schisms that could divide Reformers during this period.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.782

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0360.019
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.014
GPT teacher head0.195
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

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