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Record W2110218939 · doi:10.15353/cjds.v2i3.99

Opening Ontario’s “Saddest Chapter”: A Social History of Huronia Regional Centre

2013· article· en· W2110218939 on OpenAlexaffvenueabout
Kate Rossiter, Annalise Clarkson

Bibliographic record

VenueCanadian Journal of Disability Studies · 2013
Typearticle
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsInstitutionalisationContext (archaeology)BureaucracyNeglectClass actionGovernment (linguistics)Political scienceAction (physics)Public administrationSociologyCriminologyLawMedicineGeographyPoliticsNursingState (computer science)

Abstract

fetched live from OpenAlex

In 2010 the residents of Huronia Regional Centre, Rideau Regional Centre and Southwestern Regional Centre launched three separate class action lawsuits against the government of Ontario. These lawsuits allege that residents of these provincially-run centres, the majority of whom were diagnosed with some form of intellectual disability, were subjected to multiple forms of abuse and inhumane treatment. This paper contextualizes these lawsuits by providing a social history of the Huronia Regional Centre – the first centre to launch a class action lawsuit. The purpose is threefold: firstly, to explore the social context of Canadian institutions as exemplified by the history of Huronia Regional Centre, secondly, to outline the bureaucratic organization of institutions related to the social context of institutionalization, and thirdly, to understand the social and historical milieu that lead to the maltreatment and neglect of institutionalized persons in Ontario. As such, this paper attempts to make clear the importance of the lawsuits and other current historical justice-related pursuits undertaken by institutional survivors.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.884

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0320.020
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.119
GPT teacher head0.329
Teacher spread0.210 · 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 designQualitative
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

Citations22
Published2013
Admission routes3
Has abstractyes

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