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Record W2332227285 · doi:10.1177/0143831x14550696

Immigrants and job satisfaction: Do high performance work systems play a role?

2014· article· en· W2332227285 on OpenAlexaffabout
James Chowhan, Işık U. Zeytinoglu, Gordon B. Cooke

Bibliographic record

VenueEconomic and Industrial Democracy · 2014
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMemorial University of NewfoundlandMcMaster University
Fundersnot available
KeywordsJob satisfactionWork systemsModerationAffect (linguistics)ImmigrationWorkforcePsychologyJob designJob performanceWork (physics)BusinessSocial psychologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

This study focuses on immigrants in Canada and examines their job satisfaction as compared to Canadian-born employees. The authors explore whether high performance work systems (HPWS) affect immigrant employees’ job satisfaction differently than Canadian-born, where HPWS include empowerment, motivation and skill enhancing sub-bundles of practices. The study uses Statistics Canada’s Workplace and Employee Survey, a longitudinal dataset consisting of six years of data from 1999 to 2004 and 49,344 employees. Ordered logistic regression analyses are used to explore causal relationships. The moderation results show that increases in the motivation sub-bundle and increases in overall experience of HPWS practices are related to increases in job satisfaction among immigrants when compared to Canadian-born employees. Immigrants are a segment of the workforce that is understudied in management. This study identifies HPWS bundles that positively affect immigrants’ job satisfaction, suggesting a role for managers to capitalize on job satisfaction improvements ultimately contributing to organizational success.

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 score0.025
Threshold uncertainty score0.870

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 head0.034
GPT teacher head0.294
Teacher spread0.260 · 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

Citations22
Published2014
Admission routes2
Has abstractyes

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