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Record W2087404877 · doi:10.1108/02683941311300739

Probing into commitment's nonlinear relationships to work outcomes

2013· article· en· W2087404877 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Managerial Psychology · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversité du Québec en OutaouaisUniversité de SherbrookeCegep de Trois-RivieresCégep de SherbrookeDawson CollegeHEC Montréal
Fundersnot available
KeywordsOrganizational commitmentPsychologySocial psychologyOrganizational citizenship behaviorOriginalityValue (mathematics)Mathematics

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to investigate the possibility of curvilinear patterns of relationships between workplace affective commitment and in‐role performance, organizational citizenship behaviors and burnout. As most commitment theories assume strictly linear relations with these outcomes, demonstrating that these positive associations do not hold above some ceiling point in the commitment continuum is potentially important for research and practice. Design/methodology/approach The possibility of nonlinear relations was examined in a sample of 273 hospital employees. Findings The results yielded strong support for the authors' hypotheses. Indeed, most of the relations observed (ten of 15) between affective commitment foci and work outcomes were curvilinear, revealing a ceiling to the positive association between commitment and outcomes. Although these results vary in strength across work outcomes and commitment targets, they reveal that affective commitment has negative associations with employee productivity and psychological health at extreme levels. Originality/value Methodologically, these results illustrate the need to systematically explore the true nature of relations among constructs, even in areas where it is assumed to be well known. Practically, these results suggest that, ultimately, moderate levels of commitment may be more beneficial than extremely high levels.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.297
Teacher spread0.263 · 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