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Record W7124229790

HHRU 00:3-00:7

2000· book· en· W7124229790 on OpenAlexaboutno aff
Kazanjian, Arminée, 1947-, Wood, Laura Christine, 1955-, Harold Yip, Sherin Rahim-Jamal, Allyson Macdonald

Bibliographic record

VenuecIRcle (University of British Columbia) · 2000
Typebook
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsSoftware deploymentHuman resourcesBaseline (sea)Health careData collectionWork (physics)
DOInot available

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 II of the study, "The Supply of Nursing Personnel in Canada" examines data on the supply of nursing personnel in the provinces and territories to provide basic information about employment status, deployment (place of employment, area of responsibility, type of position, hours worked), age, and type and place of education/training. The analysis is based on data collected by the respective regulatory bodies in their registration and renewal processes. Two separate years of secondary data are utilized in the analysis (1990 and 1997), presenting a detailed national and regional picture on the supply of nurses in 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.243
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7570.649

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 head0.020
GPT teacher head0.275
Teacher spread0.255 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

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