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Record W2788644997 · doi:10.1080/1359432x.2018.1443914

The future of workplace commitment: key questions and directions

2018· article· en· W2788644997 on OpenAlexaff
Yvonne Van Rossenberg, Howard J. Klein, Kajsa Asplund, Kathleen Bentein, Heiko Breitsohl, Aaron Cohen, David Cross, Ana Carolina de Aguiar Rodrigues, Véronique Duflot, Steven Kilroy, Nima Ali, Andriana Rapti, Sascha Alexander Ruhle, Omar Solinger, Juani Swart, Zeynep Y. Yalabik

Bibliographic record

VenueEuropean Journal of Work and Organizational Psychology · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversité du Québec à Montréal
FundersUniversity of Bath
KeywordsKey (lock)SociologyPsychologyOrganizational commitmentPublic relationsSocial psychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This position paper presents the state-of-the art of the field of workplace commitment. Yet, for workplace commitment to stay relevant, it is necessary to look beyond current practice and to extrapolate trends to envision what will be needed in future research. Therefore, the aim of this paper is twofold, first, to consolidate our current understanding of workplace commitment in contemporary work settings and, second, to look into the future by identifying and discussing avenues for future research. Representative of the changing nature of work, we explicitly conceptualize workplace commitment in reference to (A) “Temporary work”, and (B) “Cross-boundary work”. Progressing from these two themes, conceptual, theoretical and methodological advances of the field are discussed. The result is the identification of 10 key paths of research to pursues, a shared agenda for the most promising and needed directions for future research and recommendations for how these will translate into practice.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.312
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

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

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 head0.023
GPT teacher head0.358
Teacher spread0.335 · 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.

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

Citations92
Published2018
Admission routes1
Has abstractyes

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