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Record W3048852567

Employment-Related Geographic Mobility of Healthcare Workers -Nova Scotia Policy Brief

2019· article· en· W3048852567 on OpenAlexaboutno aff
Lois Jackson

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2019
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaConsolidation (business)Health careBusinessStakeholderNova (rocket)Public relationsPolitical scienceEconomic growthGeographyEconomicsAccountingEngineering
DOInot available

Abstract

fetched live from OpenAlex

SUMMARY: \n• Purpose: To highlight the key insights from the worker interviews and survey component of the Employment-Related Geographic Mobility (ERGM) study of Nova Scotian healthcare workers \n• The Issue: The ERGM of Nova Scotian healthcare workers needs to be more fully considered in the development, consolidation and implementation of various policies \n• Implications: All mobile healthcare workers should have employment contracts that ensure their safety and cover all economic costs of mobility. \n• Action Requested: To create a multi-stakeholder forum to discuss the practice implications of the research findings and co-develop a responsive set of policies.

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)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.334

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0080.002
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.043
GPT teacher head0.368
Teacher spread0.326 · 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 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
Published2019
Admission routes1
Has abstractyes

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