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Record W2468066100 · doi:10.14288/1.0075954

Nursing workforce study, volume 1 : demographic context and health system structure for nursing services in Canada

2014· article· en· W2468066100 on OpenAlexaboutno aff
Arminée Kazanjian, Sherin Rahim-Jamal, Laura Christine Wood, Allyson Macdonald

Bibliographic record

VenuecIRcle (University of British Columbia) · 2014
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsWorkforceNursingContext (archaeology)MedicinePolitical scienceGeography

Abstract

fetched live from OpenAlex

This study was commissioned by the Federal/Provincial/Territorial Advisory Committee on Health Human Resources (ACHHR) to develop baseline data on the supply and education of Registered Nurses (RNs), Registered Psychiatric Nurses (RPNs), and Licensed Practical Nurses (LPNs), and on employer practices pertaining to the deployment of all patient care providers. The study results are published in five separate volumes. Volume 1 of the study "Demographic Context and Health System Structure for Nursing Services in Canada", provides a general overview of demographic and system changes; it describes the current demographic context for nursing practice and the structure of provincial/territorial health care delivery systems. The demographic analyses are based on 1996 Census data. Provincial/territorial health care delivery information for the most part are obtained from "Health System Reform in Canada, 1997," by Health Canada.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.466

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.010
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0000.001
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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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
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
Published2014
Admission routes1
Has abstractyes

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Same venuecIRcle (University of British Columbia)Same topicGlobal Health Workforce IssuesFrench-language works237,207