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Record W2464629896 · doi:10.14288/1.0075920

Life-cycle activity patterns of registered nurses in British Columbia : forecasting future supply and professional life expectancy

2014· article· en· W2464629896 on OpenAlexaboutno aff
Arminée Kazanjian

Bibliographic record

VenuecIRcle (University of British Columbia) · 2014
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLife expectancyExpectancy theoryMedicineEconomicsEnvironmental healthManagementPopulation

Abstract

fetched live from OpenAlex

Health manpower planning and in particular its quantitative research stage have not, until very recently, received much approbation as complex and necessary processes in the planning and operation of health care delivery systems. Recent efforts are mainly in the area of physician manpower. The first National Health Manpower Conference in Canada was held in October 1969 based on the belief that an attempt should be made to develop our human resources in the health field in some kind of rational manner. A rational planning approach is even more important for health care personnel than for those in primary markets, since microeconomic forces that equilibrate the latter do not apply as readily (if at all) to the health environment. There is also some evidence that nurses' market work behaviour is appreciably different from that of other health occupations due mainly to the gender factor. Nursing is a female dominated profession and considerable variation in the amount of time spent in market work exists among individuals. Thus, an in-depth study was undertaken to specifically quantify Registered Nurse (RN) supply/requirements in British Columbia and provide useful information to planners at various levels.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.029
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.266
Teacher spread0.240 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

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