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Record W2899465712 · doi:10.1177/0143831x18805848

The association between perceived personal power, team commitment and intrinsic motivation for permanent and temporary workers

2018· article· en· W2899465712 on OpenAlexaff
Jeroen P. de Jong, Christa L. Wilkin, Cristina Rubino

Bibliographic record

VenueEconomic and Industrial Democracy · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsYork University
Fundersnot available
KeywordsPerceptionAssociation (psychology)Power (physics)PsychologySample (material)Social psychologyMultilevel modelPersonal protective equipmentMedicineComputer science

Abstract

fetched live from OpenAlex

To date, research on how temporary workers are embedded in teams is limited to how they impact their co-workers with permanent contracts and how temporary workers impact team functioning and performance through power structures in teams. We know very little about how the perceptions of personal power of temporary and permanent workers affect their own motivation and commitment. This study aims to assess the relationship between perceived personal power, intrinsic motivation and team commitment for temporary versus permanent workers. Drawing on Conservation of Resources Theory, the authors propose that this association is non-linear for temporary workers and linear for permanent workers. They test these assumptions using a sample of 64 temporary and 275 permanent workers nested in 58 teams. Multilevel analyses show that for temporary workers, the association between personal power perceptions and intrinsic motivation and team commitment flattens at moderate to high levels of perceived personal power. For permanent workers, the study finds a linear relationship. Implications for theory 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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.999

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 studies0.0020.000
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 head0.071
GPT teacher head0.340
Teacher spread0.269 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

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