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Record W3025753304

Identity development of second-generation Chinese Canadians through heritage and dominant cultures

2020· dissertation· en· W3025753304 on OpenAlexaboutno aff
Tiffany Wu

Bibliographic record

VenueNational University System Repository (National University System) · 2020
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Gender studiesSociologyAnthropologyGenealogyPolitical scienceGeographyHistoryAestheticsArt
DOInot available

Abstract

fetched live from OpenAlex

This paper addresses the experiences of second-generation Chinese Canadians in developing their identity through heritage and dominant cultures. Literature on global migration and dual nation identities is explored before discussing the dichotomy of collectivism and individualism, which highlights a distinction between focusing on community goals compared to autonomy. The negotiation between heritage and dominant cultures is further impacted by a range of factors, including specific cultural values such as filial piety, as well as parental attitudes and components of ethnic identity (e.g. self-labels and language). Reviewing the existing, albeit limited, literature on Chinese Canadians has emphasized the shortcomings of data on this demographic and the lack of information on a population that has deep-rooted historical and unique connections with Canada. Amongst the studies available, the results have painted a picture riddled with a blend of generational statuses, a hyperfocus on adolescent individuals, and sampling mostly limited to metropolitan communities. Recognizing the complexities faced by second-generation Chinese Canadians, practitioners are required to acknowledge the unique experiences and local resources pertaining to this group of people. Further, self-awareness and cultural competencies strengthen the ability to align with prospective clients. Implications for the helping professionals and considerations for future studies are discussed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.015
GPT teacher head0.244
Teacher spread0.229 · 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 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
Published2020
Admission routes1
Has abstractyes

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