MétaCan
Menu
Back to cohort
Record W2237520619 · doi:10.1002/job.2094

Location, location, location: Contextualizing workplace commitment

2016· article· en· W2237520619 on OpenAlexaff
S. Arzu Wasti, Mark Peterson, Heiko Breitsohl, Aaron Cohen, Frances Jørgensen, Ana Carolina de Aguiar Rodrigues, Qingxiong Weng, Xiaohong Xu

Bibliographic record

VenueJournal of Organizational Behavior · 2016
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsRoyal Roads University
FundersFlorida Atlantic University
KeywordsPsychologyOrganizational commitmentSocial psychologyPublic relationsBusinessPolitical science

Abstract

fetched live from OpenAlex

Summary The purpose of the present commentary is to discuss the nature and correlates of workplace commitment across cultures. We asked six organizational behavior scholars, who are intimately familiar with Brazil, China, Denmark, Germany, or Israel as their country of origin or extended residence, to “contextualize” workplace commitment. They did so by explicating institutional and cultural characteristics of their context on the emergence, meaning, and evolution of commitment by reference to their own research and extant local research. Their responses not only supported the utility of three‐component model of commitment but also revealed the differential salience of various commitment constructs (e.g., components and foci of commitment) as well as possible contextual moderators on the development and outcomes of commitment. The commentators also described changes including the growing prevalence of multicultural workforces within national borders and changes in employment relationships and cultural values in their national contexts and considered future research directions in culture and commitment research. Copyright © 2016 John Wiley & Sons, Ltd.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.382
Teacher spread0.331 · 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 teacher head, not a consensus.

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

Citations54
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Organizational BehaviorSame topicEmployment and Welfare StudiesFrench-language works237,207