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Record W1709018304 · doi:10.3138/cbmh.29.1.101

“The older staff, myself included, we were pretty institutionalized ourselves”: Authority and Insight in Practitioner Narratives of Psychiatric Deinstitutionalization in Prairie Canada

2012· article· en· W1709018304 on OpenAlexaffvenueabout
Chris Dooley

Bibliographic record

VenueCanadian Journal of Health History · 2012
Typearticle
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsYork University
Fundersnot available
KeywordsPaternalismInstitutionalisationNarrativeHegemonyWelfareTransformative learningSociologyMedicineNursingPolitical sciencePsychiatryLawPolitics

Abstract

fetched live from OpenAlex

In the early 1960s, Canada's provinces began radically to reduce the in-patient populations of their psychiatric services. This was part of a wider project of trans-institutionalization through which vulnerable people and those who cared for them were shifted across institutional contexts within Canada's evolving welfare state apparatus. This article draws on interviews with Psychiatric Nurses who worked through the transformative mental health reforms of the 1960s and 1970s, and it makes a case for practitioner history. Practitioner narratives offer a window on the vital tensions between the manifest and the latent functions of welfare institutions, between the impulse to support and the impulse to control, and between paternalism and respect for the rights of the mentally ill. It draws upon the authority of practitioners who, retrospectively, have gained insight into their involvement with prior regimes of caring and control and have come to discern institutional logics previously so hegemonic as to have been largely invisible to them.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.788
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.319
Teacher spread0.284 · 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 teacher head, 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

Citations4
Published2012
Admission routes3
Has abstractyes

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