MétaCan
Menu
Back to cohort
Record W4383535183 · doi:10.3390/healthcare11131954

The Crisis in the Nursing Labour Market: Canadian Policy Perspectives

2023· article· en· W4383535183 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealthcare · 2023
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFinancial crisisBusinessNursingLabour economicsEconomicsMedicineMacroeconomics

Abstract

fetched live from OpenAlex

The labour market for care professionals has experienced significant changes, resulting in critical shortages globally. Nurses represent the largest share of health workers worldwide; nonetheless, an estimated 13 million more nurses will be needed over the next 10 years. Prior to the pandemic, the domestic supply of nurses in Canada had not kept pace with the ever-increasing demand for services. Pre-pandemic age- and needs-based forecasting models have estimated shortages in an excess of 100,000 nurses nationwide by 2030. While COVID-19 has accelerated the demand for and complexity of service requirements, it has also resulted in losses of healthcare professionals due to an increased sick leave, unprecedented burnout and retirements. This paper examines key factors that have contributed to nursing supply issues in Canada over time and provides examples of policy responses to the present shortage facing the healthcare system. To provide adequate care, the nursing workforce must be stabilized and-more importantly-recognized as critical to the health of the population.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.466
Teacher spread0.396 · 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