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Record W2090191000 · doi:10.1037/a0020372

Attachment at (not to) work: Applying attachment theory to explain individual behavior in organizations.

2010· article· en· W2090191000 on OpenAlexafffund
David A. Richards, Aaron C. H. Schat

Bibliographic record

VenueJournal of Applied Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsMcMaster UniversityLakehead University
FundersSocial Sciences and Humanities Research Council of CanadaLakehead University
KeywordsPsychologyCounterproductive work behaviorOrganizational citizenship behaviorSocial psychologyAttachment theoryOrganizational behaviorWork behaviorOrganizational commitmentNegative affectivityPositive affectivityTurnoverWork (physics)Developmental psychologyPersonality

Abstract

fetched live from OpenAlex

In this article, we report the results of 2 studies that were conducted to investigate whether adult attachment theory explains employee behavior at work. In the first study, we examined the structure of a measure of adult attachment and its relations with measures of trait affectivity and the Big Five. In the second study, we examined the relations between dimensions of attachment and emotion regulation behaviors, turnover intentions, and supervisory reports of counterproductive work behavior and organizational citizenship behavior. Results showed that anxiety and avoidance represent 2 higher order dimensions of attachment that predicted these criteria (except for counterproductive work behavior) after controlling for individual difference variables and organizational commitment. The implications of these results for the study of attachment at work are discussed.

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)0.006
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 score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.408
Teacher spread0.378 · 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

Citations282
Published2010
Admission routes2
Has abstractyes

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