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Record W2283373875 · doi:10.1177/0002764215580585

Social Networks in East and Southeast Asia I

2015· article· en· W2283373875 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Behavioral Scientist · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGuanxiKinshipContext (archaeology)ChinaSocial capitalSociologySocial network (sociolinguistics)SocialismHierarchyInterpersonal tiesPolitical sciencePolitical economySocial sciencePoliticsGeographyCommunismLaw

Abstract

fetched live from OpenAlex

These articles examine social networks in the context of Asia. Their pages contain numerous examples showcasing the primacy of social context in the patterning, accumulation, role, and value of social networks and social capital. Network characteristics follow from national and institutional characteristics: In China, kinship networks are prominent all throughout the life course. Meanwhile, guanxi continues to be an important factor in the labor market and academic success of Chinese individuals, despite the shift from socialism to capitalism. In Japan, mutual monitoring among kin and coworkers make for a society based on strong ties. In Korea, voluntary associations are important communal spaces for meeting diverse contacts. In China’s neighborhoods, cooperation between neighbors coexists with social control from above to reinforce social hierarchy. The issue ends with a note about the importance of cultivating guanxi in organizations and in everyday life.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
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 head0.066
GPT teacher head0.356
Teacher spread0.291 · 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