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Record W2765335485 · doi:10.1111/emre.12149

Social Support and Life‐Domain Interactions among Assigned and Self‐Initiated Expatriates

2017· article· en· W2765335485 on OpenAlexaff
Felix Ballesteros Leiva, Gwénaëlle Poilpot‐Rocaboy, Sylvie St‐Onge

Bibliographic record

VenueEuropean Management Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsHEC Montréal
FundersLG Display
KeywordsDomain (mathematical analysis)PsychologySocial lifeIMesPersonal lifeSocial psychologySocial supportFamily lifeSociologyPolitical scienceGender studiesSocial science

Abstract

fetched live from OpenAlex

Based upon conservation of resources theory, this study is the first to explore (1) the relations between life‐domain support received by internationally mobile employees (IMEs) from their organization, supervisors, coworkers, and family and friends and their life‐domain conflicts and enrichments in two directions: work life → personal life (WL → PL) and personal life → work life (PL → WL) and (2) whether these links are different between assigned expatriates (AEs) and self‐initiated expatriates (SIEs). The questionnaire data were collected from 182 SIEs and 102 AEs. Results from multivariate analyses show that (1) the more IMEs perceive receiving life‐domain support from their family and friends and their organization, the less they report life‐domain conflicts and (2) the more IMEs perceive receiving life‐domain support from their coworkers, the more they report life‐domain enrichments. Finally, it appears that AEs' perceived life‐domain organizational support is positively related to their perceived WL → PL enrichments and that SIEs' perceived life‐domain coworker support is negatively related to their life‐domain conflicts in both directions.

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)0.005
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.068
GPT teacher head0.372
Teacher spread0.304 · 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

Citations20
Published2017
Admission routes1
Has abstractyes

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