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Record W3122446913

Combined Effects of the Three Commitment Components on Focal and Discretionary Behaviors: A Test of Meyer and Herscovitch's Propositions

2005· article· en· W3122446913 on OpenAlexaff
Ian R. Gellatly, John P. Meyer, Andrew A. Luchak

Bibliographic record

VenueSSRN Electronic Journal · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsWestern UniversityUniversity of Alberta
Fundersnot available
KeywordsContinuancePsychologySocial psychologyNormativeMeaning (existential)Construct (python library)Context (archaeology)Test (biology)Organizational commitmentOrganizational citizenship behaviorSample (material)Function (biology)Political scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to test theoretical propositions advanced by Meyer and Herscovitch (2001) concerning the interactive effects of affective, normative, and continuance commitment on focal (staying intentions) and discretionary (citizenship) behavior. Study measures were gathered from a sample of 545 hospital employees. Several a priori predictions regarding commitment profile differences were confirmed. Significant three-way interactions were found for both staying intentions and citizenship behavior. The pattern of relations for both behavioral criteria partially confirmed the hypotheses, but also provided evidence of possible “context effects” whereby the meaning and implications of the commitment components varies as a function of the other components. These effects were most notable for normative commitment and may offer new insight into the nature of this construct. Implications for commitment theory and its application were 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)0.010
metaresearch head score (Gemma)0.044
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 score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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