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Record W2023407318 · doi:10.1177/1043659604270980

Applying a Cultural Lens to the Concept of Burnout

2004· review· en· W2023407318 on OpenAlexaff
Janet E. Raiger

Bibliographic record

VenueJournal of Transcultural Nursing · 2004
Typereview
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsLambton College
Fundersnot available
KeywordsBurnoutEmotional exhaustionPerspective (graphical)Organizational culturePsychologyNursingRelevance (law)Social psychologyMedicineClinical psychologyPublic relationsPolitical science

Abstract

fetched live from OpenAlex

Burnout is a unique type of stress syndrome that is pervasively affecting the nursing profession. The literature on burnout is reviewed, and a conceptual framework using Maslach's Burnout Inventory is provided. The culture of organizations is examined with regard to its contribution to the antecedents and consequences of burnout. Leininger's cultural care theory and its relevance to the concept of burnout and culture is discussed. Implications for the amelioration of burnout from the perspective of culture are discussed to stimulate future changes in nursing administration, practice, and education. A culture of trust, support, open communication, and respect can foster healthy work environments and protect against burnout.

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)0.004
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.010
Science and technology studies0.0020.009
Scholarly communication0.0040.006
Open science0.0020.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.156
GPT teacher head0.503
Teacher spread0.347 · 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
GenreReview

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

Citations50
Published2004
Admission routes1
Has abstractyes

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