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Making Sense of Work Life: A Structural Model of Burnout

2010· article· en· W2057451841 on OpenAlexaff
Michael P. Leiter, Santiago Gascón, Begoña Martínez‐Jarreta

Bibliographic record

VenueJournal of Applied Social Psychology · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsAcadia University
Fundersnot available
KeywordsBurnoutConformityPsychologyOrganizational justiceMediationWork (physics)Social psychologyEconomic JusticeApplied psychologyOrganizational commitmentSociologyPolitical scienceClinical psychology

Abstract

fetched live from OpenAlex

Hospital‐based nurses (N = 832) and doctors (N = 603) in northern and eastern Spain completed a survey of job burnout, areas of work life, and management issues. Analysis of the results provides support for a mediation model of burnout that depicts employees' energy, involvement, and efficacy as intermediary experiences between their experiences of work life and their evaluations of organizational change. The key element of this model is its focus on employees' capacity to influence their work environments toward greater conformity with their core values. The model considers 3 aspects of that capacity: decision‐making participation, organizational justice, and supervisory relationships. The analysis supports this model and emphasizes a central role for first‐line supervisors in employees' experiences of work life.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.034
GPT teacher head0.319
Teacher spread0.285 · 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 designSimulation or modeling
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

Citations94
Published2010
Admission routes1
Has abstractyes

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