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Record W2032646436 · doi:10.1177/011719680701600203

At the End of the World: Holding on to Health Workers in Niue

2007· article· en· W2032646436 on OpenAlexaboutno aff
John Connell

Bibliographic record

VenueAsian and Pacific migration journal · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
Fundersnot available
KeywordsWorkforceQuarter (Canadian coin)PopulationBusinessDemographic economicsPromotion (chess)Economic growthLabour economicsPolitical scienceGeographyEconomicsSociologyPoliticsDemography

Abstract

fetched live from OpenAlex

The migration of health workers from Niue is part of a broader migration trend where the national population has declined significantly in the past quarter of a century. This is due to significant social and economic differences with New Zealand, and the shift in population gravity towards New Zealand where most Niueans now live. The impact of migration in isolated Niue was less than in some other Pacific states, measured either as workforce vacancies or inadequate service provision. Niue has retained an effective health workforce because of external conditions: an aid dependence that enables a large public service with most households having two wage earners in the public service. Opportunities for promotion and training, alongside boredom, rather than salaries or standard workplace issues concerned many workers. Small and remote islands such as Niue face the challenge to retain a skilled workforce in the face of high rates of emigration.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.003
Scholarly communication0.0050.004
Open science0.0010.009
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0260.002

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 head0.017
GPT teacher head0.304
Teacher spread0.287 · 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 designQualitative
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

Citations17
Published2007
Admission routes1
Has abstractyes

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