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Nurses' Experiences of Restructuring in Three Ontario Hospitals

2001· article· en· W2161227790 on OpenAlexaffabout
Jennifer Blythe, Andrea Baumann, Phyllis Giovannetti

Bibliographic record

VenueJournal of Nursing Scholarship · 2001
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of AlbertaMcMaster University
Fundersnot available
KeywordsRestructuringEmpowermentNursingBureaucracyWork (physics)Focus groupPsychologyMedicineBusinessPolitical scienceMarketing

Abstract

fetched live from OpenAlex

PURPOSE: To describe the effects of restructuring, particularly redeployment, on nurses' personal and work lives, and to compare the utility of "survivor syndrome" and empowerment as alternative concepts for understanding these effects and planning change. METHODS: Twenty-six focus groups or interviews were held with 59 nurses working in three hospitals in Ontario, Canada. FINDINGS: Participants described how restructuring strategies had affected them as individuals, as members of nursing teams, and as employees. In each of these aspects of their work lives, relationships became less integrated, their work activities became less controllable, and the changes compromised their ability to deliver effective care. CONCLUSIONS: Restructuring intensifies structural weaknesses in professions, such as nursing, whose members are primarily employed by bureaucracies. Nurses may not find survivor syndrome a useful model to explain their low morale following restructuring because it identifies nurses as "patients" in need of therapy. An empowerment model that takes into account nurses' concerns about uncertainty and integration may be more fruitful for devising strategies to enhance their ability to practice effectively in hospital settings.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.043
GPT teacher head0.345
Teacher spread0.302 · 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 teacher head, 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

Citations81
Published2001
Admission routes2
Has abstractyes

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