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Record W2083030664 · doi:10.1080/09585192.2013.763838

Expatriate pay satisfaction: the role of organizational inequities, assignment stressors and perceived assignment value

2013· article· en· W2083030664 on OpenAlexaff
Margaret A. Shaffer, Barjinder Singh, Yu‐Ping Chen

Bibliographic record

VenueThe International Journal of Human Resource Management · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsConcordia University
Fundersnot available
KeywordsExpatriateOrganizational justiceStressorEquity (law)Equity theoryValue (mathematics)PsychologyProcedural justiceSocial psychologyEconomic JusticeNoveltyInteractional justiceSample (material)Job satisfactionBusinessOrganizational commitmentEconomicsPolitical sciencePerceptionMicroeconomics

Abstract

fetched live from OpenAlex

Using equity, stress and buffer theories, we investigate the role played by organizational inequities (organizational justice and provision of benefits) and assignment stressors (work adjustment and role novelty) in predicting expatriate pay satisfaction. We also assess the role of perceived assignment value as an important buffer that moderates the above relationships. With a sample of 78 expatriates from nine nationalities working in Hong Kong, we find that organizational justice and work adjustment are both positively related to expatriate pay satisfaction. We also find that perceived assignment value strengthens the provision of benefits–pay satisfaction and work adjustment–pay satisfaction relationships. Limitations and managerial implications 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 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)0.002
metaresearch head score (Gemma)0.007
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.274
Teacher spread0.261 · 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

Citations15
Published2013
Admission routes1
Has abstractyes

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