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Record W2268842462 · doi:10.12927/hcq.2016.24477

Relentless Incrementalism: Shifting Front-Line Culture from Institutional to Recovery Oriented Mental Healthcare

2016· article· en· W2268842462 on OpenAlexaffabout
Deborah Corring, Jennifer Speziale, Nina Desjardins, Abraham Rudnick

Bibliographic record

VenueHealthcare Quarterly · 2016
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsSt. Joseph’s Healthcare HamiltonCentre for Addiction and Mental Health
Fundersnot available
KeywordsIncrementalismFront lineMental healthcareMental healthHealth careFront (military)Mental health careLine (geometry)Organizational cultureHealth administrationNursingPublic administrationPsychologyPolitical scienceBusinessMedicinePublic relationsPsychiatryEngineeringLaw

Abstract

fetched live from OpenAlex

St. Joseph's Health Care London is a publicly funded hospital that has led mental health service system transformation in south west Ontario following directives from the Health Services Restructuring Commission (HSRC). This paper documents how provincial policy, HSRC directives, organizational planning, research projects, quality initiatives and change management activities drove, shaped and accomplished a cultural shift at the front line to recovery-focused care. Simultaneous to these activities, beds and related ambulatory services were divested to four other hospitals, beds and employment services were closed and two new, state-of-the-art facilities were constructed, adding considerable complexities to achieving cultural change. This paper documents the incremental steps that were taken to achieve that change.

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)0.015
metaresearch head score (Gemma)0.018
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 score0.018
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.025
Scholarly communication0.0140.006
Open science0.0020.015
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.117
GPT teacher head0.398
Teacher spread0.281 · 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

Citations2
Published2016
Admission routes2
Has abstractyes

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