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Record W2089389474 · doi:10.3917/spub.042.0251

Le marché du travail en soins infirmiers au Canada (1985-1999)

2004· review· fr· W2089389474 on OpenAlexaffabout
Gilles Dussault, Martine Fournier, Margareth Santos Zanchetta, S Kérouac, Jean‐Louis Denis, L Bojanowski, Maud Carpentier, Moryssa Grossman

Bibliographic record

VenueSanté Publique · 2004
Typereview
Languagefr
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceSociology

Abstract

fetched live from OpenAlex

This literature review analysed both published and unpublished scientific and professional studies on the nursing labour market in Canada within the period of 1985 to 1999. The goal was to conduct a situational analysis utilising statistical data and canvassing all concerned parties to extract their points of view. The analysis revealed significant cyclical variations in the evolution of the workforce, particularly with respect to auxiliary nurses, such as the perceived existence of major problems in recruiting new professionals in the field and retaining existing professionals in their organisations, the lack of homogeneity in educational training programmes, and the co-existence of several operational structures for organising nursing care, of which there is a lack of evaluation on their effectiveness. The results of the literature review identify the necessity to further develop the knowledge base on such a relevant dimension of the nursing labour market.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score0.348

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.030
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.387
Teacher spread0.353 · 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 designObservational
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

Citations2
Published2004
Admission routes2
Has abstractyes

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