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Record W1484275202

Constructing Identity: Stories of Canadian Parents Bringing up Children adopted from China- The role of heritage culture and language

2008· article· en· W1484275202 on OpenAlexaboutno aff
Fang Bian

Bibliographic record

VenueoURspace (University of Regina) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)ChinaHeritage languageSociologyGender studiesLinguisticsPolitical scienceAestheticsLawPedagogyArt
DOInot available

Abstract

fetched live from OpenAlex

International adoption is increasing rapidly during the last two decades in Canada and United States. Canadian families with children adopted from China have been leading the statistics of the international adoption in Canada. For the last decade, it steadily made up over half of the international adoptions. Despite of the growing population of the children adopted internationally and interracially, relatively little is known about their social and cultural identity development after their arrival. The presentation will share the parents’ perspective on the meaning of heritage language and culture to the well-being of the children adopted interracially and their adopting families. Some selected literature review and some findings of interviews with the adoptive parents will be discussed. More and more Canadian parents are bringing up children adopted transracially, and over half of these children are from China. How the parents see the role of heritage culture and language playing the identity development of these children will be shared in the presentation.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.238
Threshold uncertainty score0.479

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0350.012
Scholarly communication0.0050.003
Open science0.0030.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.276
Teacher spread0.260 · 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
Published2008
Admission routes1
Has abstractyes

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