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Record W2795574175 · doi:10.1163/22125868-12340078

Elitist in Façade

2017· article· en· W2795574175 on OpenAlexaffabout
Hongxia Shan

Bibliographic record

VenueInternational Journal of Chinese Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTransnationalismCapitalismChinaPolitical scienceSociologyGender studiesPolitics

Abstract

fetched live from OpenAlex

Drawing on a qualitative study of a group of professional Chinese women navigating their career lives between China and Canada, this paper addresses how Chinese transnationalism is constituted within global capitalism. It starts by mapping the career lives of the Chinese immigrant women. Their experiences point to the emergence of a transnational field between Canada and China where skill/labor and capital conjoin in distinct ways. The study further shows that this transnational social field is comprised of a complex of social relations reticulated through multiple institutions, organizations, and actors. Although the interest of economic accumulation and Western-centric social and cultural orders are predominant in shaping the women’s career spaces, this transnational field also provides conduits for alternative flows of power, privileging the entrepreneurial quest for social, cultural, and economic capitals. Despite its elitist façade, the transnational field is itself also vulnerable, fractured, and prone to crisis.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0140.022
Scholarly communication0.0050.005
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.019
GPT teacher head0.395
Teacher spread0.376 · 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 designQualitative
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

Citations0
Published2017
Admission routes2
Has abstractyes

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