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Record W2053491256 · doi:10.2466/pr0.2000.87.3.1013

Hospital Restructuring and Downsizing in Canada: Are Less Experienced Nurses at Risk?

2000· article· en· W2053491256 on OpenAlex
Ronald J. Burke, Esther R. Greenglass

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

VenuePsychological Reports · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsYork University
Fundersnot available
KeywordsRestructuringNursingTeam nursingMedicineNursing staffEconomic shortagePrimary nursingHealth carePsychologyNurse educationPolitical science

Abstract

fetched live from OpenAlex

The health care sector has undergone significant change during the past decade as hospitals struggle to provide the same service with fewer resources. This study examined perceptions of hospital restructuring and downsizing and their effects on nursing staff as a function of years in nursing. Data were obtained from 1,362 staff nurses by questionnaire. Nursing staff having less tenure generally described and responded to hospital restructuring and downsizing in more negative terms. Nursing staff having less tenure were in better health, reflecting their younger age. Some implications for hospital administration and the nursing profession are raised. Entrants to hospital-based nursing staff positions are the life blood of the profession. Their reactions to hospital restructuring and downsizing may influence their commitment to nursing as well as hospital functioning. The profession may have difficulty attracting young women and men into nursing programs. As longer tenured nursing staff retire, a potential shortage of nurses may result.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.150
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.128
GPT teacher head0.409
Teacher spread0.281 · 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