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Record W2071944827 · doi:10.1163/17932548-12341249

Calgary’s Chinese Kinship Associations: Their Role in Chinese Canadian Integration

2013· article· en· W2071944827 on OpenAlexaboutno aff
Lloyd Sciban, Lloyd Wong

Bibliographic record

VenueJournal of Chinese Overseas · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsKinshipChinaImmigrationMainstreamFictive kinshipFace (sociological concept)SociologyChinese societySettlement (finance)Gender studiesGenealogyPolitical scienceHistorySocial scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

Abstract The kinship associations in Calgary’s Chinese community were formed to assist Chinese immigrants in meeting their needs, such as housing and moral support, in the face of the discrimination they encountered during their early days of settlement in the city. In providing for these needs the kinship associations helped Chinese immigrants establish themselves, and thus, integrate into Canadian society. However, over time the opportunities to integrate into the Canadian society have increased and the question arises whether the kinship associations have been willing or able to take advantage of these opportunities. The purpose of this paper is to determine whether kinship associations in Calgary’s Chinese community are effectively promoting Chinese Canadian integration into mainstream society. Personal face-to-face interviews revealed the records of the kinship associations in integrating their members into Canadian society; these records were then compared with those of newer, non-kinship Chinese Canadian associations. The authors conclude that the integration efforts by the kinship associations are inadequate as compared to newer Calgary Chinese organisations, and that the integrative role of these kinship associations has diminished over time.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.274
Teacher spread0.262 · 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.

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

Citations2
Published2013
Admission routes1
Has abstractyes

Explore more

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