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Record W2032247124 · doi:10.1177/0265407509347930

Attachment orientations and job burnout: The mediating roles of team cohesion and organizational fairness

2009· article· en· W2032247124 on OpenAlexaff
Sigalit Ronen, Mario Mikulincer

Bibliographic record

VenueJournal of Social and Personal Relationships · 2009
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsConcordia University
Fundersnot available
KeywordsPsychologyBurnoutGeneralizability theoryStructural equation modelingSocial psychologyCohesion (chemistry)Work engagementAnxietyClinical psychologyWork (physics)Developmental psychology

Abstract

fetched live from OpenAlex

The current study explored the mediating effect of perceived work team cohesion and organizational fairness on the link between adult attachment and job burnout in a sample of 393 Israeli employees. Structural equation modeling revealed that attachment anxiety and avoidance were related to more job burnout, that the link between avoidance and burnout was fully mediated by lower appraisals of organizational fairness, and that the link between anxiety and burnout was partially mediated by lower appraisals of team cohesion. Thus, attachment insecurities were associated with negative perceptions of team cohesion and organizational fairness which, in turn, contributed to job burnout. Results were discussed based on attachment theory while emphasizing the need for further research examining the generalizability of the findings.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.358
Teacher spread0.328 · 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 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

Citations72
Published2009
Admission routes1
Has abstractyes

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