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Record W4402875430 · doi:10.1080/02529203.2024.2403269

Memory, Identity and Cross-Cultural Communication: The Evolution of the Image of Chinese Railway Workers in Canada and the Reconstruction of Multiculturalism

2024· article· en· W4402875430 on OpenAlexaboutno aff
Qu Guiping

Bibliographic record

VenueSocial Sciences in China · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismIdentity (music)SociologyCultural identityGender studiesPolitical scienceAestheticsArtSocial science

Abstract

fetched live from OpenAlex

International migrants confront many new challenges from the impact of global populism and geopolitics, but we also see the growth of a new identity culture. The Chinese community in Canada constructs its identity through the collective memory of the image of Chinese railway workers, and realizes the cross-cultural communication of a new identity culture in the course of the interaction of symbolic cultural practices. Since the 1980s, the image of Chinese railway workers has changed from “the indispensable evil” to “pioneers in nation-building” and “a tragic group subjected to injustice.” This is a product of the collective memory of the Chinese ethnic group’s pursuit of identity in Canada’s multicultural reconstruction. The Chinese ethnic group has reshaped an image of Chinese railway workers that has been widely disseminated through cross-cultural means. They have aimed at gaining social acceptance and fundamental recognition of a Chinese-Canadian identity with the help of their “native cultural heritage and historical resources” in Canada. The construction of this identity culture through collective memory has consolidated the foundations of multiculturalism.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.010
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.298
Teacher spread0.288 · 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
Published2024
Admission routes1
Has abstractyes

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