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Record W2410506693

Finding temporary relief: strategy for nursing recruitment in northern aboriginal communities.

2004· article· en· W2410506693 on OpenAlexaffabout
Bruce Minore, Margaret Boone, Mary Ellen Hill

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsLakehead University
Fundersnot available
KeywordsPreparednessEconomic shortageIncentiveNursingSample (material)PopulationNorthern territoryMedicineGeographySocioeconomicsEnvironmental healthPolitical scienceSociologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

To address a recurring shortage of nurses in the aboriginal communities of Northwestern Ontario, the First Nations and Inuit Health Branch, Health Canada, commissioned a study to explore the viability of establishing a relief pool among nurses from nearby small industrial towns. An open/close-ended survey completed by a random sample of 237 nurses from the target population documented levels of awareness, willingness, and preparedness for northern practice, as well as recruitment incentives and disincentives. Findings demonstrate an awareness of the overlap between the professional and personal dimensions characteristic of such practices, and suggest support for innovative rotations that would cut across federal/provincial/community jurisdictions. Although complex, given time and willingness, a regional relief system seems viable.

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)0.015
metaresearch head score (Gemma)0.017
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0110.002
Scholarly communication0.0020.002
Open science0.0030.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.003

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 head0.219
GPT teacher head0.467
Teacher spread0.248 · 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

Citations9
Published2004
Admission routes2
Has abstractyes

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