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Record W2792990367 · doi:10.5539/mas.v12n3p105

The Influence of Perceived Organizational Support and Work Adjustment on the Employee Performance of Expatriate Teachers in Thailand

2018· article· en· W2792990367 on OpenAlexvenueno aff
Khahan Na-Nan, Jamnean Joungtrakul, Auemporn Dhienhirun

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEmployee Performance and Management
Canadian institutionsnot available
FundersRajamangala University of Technology Thanyaburi
KeywordsExpatriateContext (archaeology)PsychologyWork (physics)Perceived organizational supportEmpirical researchSocial psychologyOrganizational commitmentPolitical scienceStatisticsMathematicsGeography

Abstract

fetched live from OpenAlex

This study investigated the influence of perceived organizational support (POS) and work adjustment (WA) on the employee performance (EP) of expatriate English teachers in Thailand. A quantitative method was used; self-evaluation data were collected from 210 expatriate English teachers working in Thailand. The results of the study confirm the hypothesized positive correlational effect of POS and WA on EP. The empirical results confirm the model of investigation consisting of POS, WA and EP developed for testing in the context of Thailand. It also challenges the established connection of POS and WA of EP in a well-understood context of antecedence and is relevant for policymakers, workers, and managers, with implications for future research.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.262
Teacher spread0.246 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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