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Record W2785452608 · doi:10.1163/17932548-12341357

Exploring Guanxi in a Cross-Cultural Context

2017· article· en· W2785452608 on OpenAlexaff

Bibliographic record

VenueJournal of Chinese Overseas · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsCarleton University
Fundersnot available
KeywordsGuanxiContext (archaeology)NarrativeChinaSociologyAsian studiesGender studiesPolitical scienceGeographyLaw

Abstract

fetched live from OpenAlex

Abstract Using a case study of recently arrived Cantonese-speaking migrants, this article examines the role of guanxi in shaping Chinese newcomers’ economic activities and opportunities in South Africa. In Johannesburg, Cantonese-speaking migrants tend to be employed in restaurant and fahfee (gambling) sectors, which are partially inherited from the early generations of South African Chinese. Through narratives and stories, this article reveals that Cantonese newcomers often strengthen personal and employment relationships through the practice of guanxi , but that doing so can also constrain their employment decisions. Moreover, the ambiguous boundary between the act of bribery and the practice of guanxi may facilitate Chinese participation but can also result in the victimization of the newcomers.

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)0.001
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 score0.046
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.004
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 head0.115
GPT teacher head0.391
Teacher spread0.276 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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