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Record W3208837238 · doi:10.3917/rsi.146.0007

L’outil d’évaluation multi-clientèle comme mécanisme de contrôle des soins à domicile : une analyse poststructuraliste

2021· review· fr· W3208837238 on OpenAlexaffabout
Pier‐Luc Turcotte, Dave Holmes, Amélie Perron

Bibliographic record

VenueRecherche en soins infirmiers · 2021
Typereview
Languagefr
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of OttawaUniversité de Sherbrooke
Fundersnot available
KeywordsAutonomyNegotiationOpposition (politics)Valuation (finance)PoliticsNursingSociologyMedicinePolitical scienceBusinessLawSocial science

Abstract

fetched live from OpenAlex

INTRODUCTION AND BACKGROUND: In Quebec (Canada), the Multi-clientele Assessment Tool (Outil d'évaluation multi-clientèle, OEMC) profoundly transformed the practice of home care professionals (HCP), including nurses. Since 2015, all home care patients with a completed OEMC have been counted to assess the performance of services. If performance targets are not reached, funding renewal is threatened, exerting pressure on HCPs. OBJECTIVE: The objective of this article is to review the OEMC's implementation in order to understand its political nature and its impacts on the practice of HCPs and patients' lives. MATERIAL AND METHOD: Drawing on the works of Michel Foucault and Gilles Deleuze, we propose a poststructuralist analysis of OEMC documents. RESULTS: Shifting from disciplinary societies to societies of control, the OEMC insidiously contributes to the regulation of home care services as well as patients' lives. The will of HCPs to apply their field of expertise is in opposition with the OEMC's purposes. DISCUSSION AND CONCLUSION: To not complete the OEMC when it is deemed unnecessary would require a negotiation by HCPs. However, HCPs' autonomy is compromised by discourses repressing all forms of resistance.

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)0.012
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0020.001

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 head0.568
GPT teacher head0.550
Teacher spread0.019 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2021
Admission routes2
Has abstractyes

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