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Record W2054334161 · doi:10.1177/0020872808099730

Intersecting social capital and Chinese culture

2009· article· fr· W2054334161 on OpenAlexaff
Miu Chung Yan, Ching Man Lam

Bibliographic record

VenueInternational Social Work · 2009
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGuanxiMainland ChinaSocial capitalChinaCapital (architecture)HumanitiesSociologyPolitical scienceEthnologySocial scienceGeographyArt

Abstract

fetched live from OpenAlex

English For youths to seek employment, social capital is as important as human capital. This article conceptually examines how guanxi, a form of social capital in Chinese culture, may be instrumental in helping young people access jobs. Suggestions of alternative services for helping unemployed youths in Mainland China, Taiwan and Hong Kong are offered. French Pour les jeunes à la recherche d’un emploi, le capital social est aussi important que le capital humain. Cet article examine comment la notion de guanxi, une forme de capital social dans la culture chinoise, peut aider concrètement les jeunes gens à avoir accès à un emploi. Il propose aussi des suggestions de services alternatifs pour aider les jeunes chômeurs en Chine, à Taïwan et à Hong-Kong. Spanish Para la juventud que busca empleo, el capital social es tan importante como el capital humano. Este artículo examina conceptualmente cómo guanxi, forma de capital social en la cultura China, puede ayudar instrumentalmente a la gente joven para acceder al trabajo. Se ofrecen recomendaciones de servicios alternativos para ayudar a la juventud desempleada en Mainland China, Taiwán y Hong Kong.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
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 head0.012
GPT teacher head0.307
Teacher spread0.295 · 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

Citations12
Published2009
Admission routes1
Has abstractyes

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