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Record W4376645809 · doi:10.1080/1070289x.2023.2213940

Intercultural sensitivity at work: oral histories of the first-generation Serbian immigrants to multicultural Canada

2023· article· en· W4376645809 on OpenAlexaboutno aff
Milena Kaličanin, Saša Trenčić

Bibliographic record

VenueIdentities · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsSerbianMulticulturalismImmigrationDiasporaGender studiesHybridityDiversity (politics)Identity (music)SociologyCultural diversityPolitical scienceCroatianAnthropologyLawAestheticsLinguisticsArt

Abstract

fetched live from OpenAlex

This article aims to problematize the concept of Canadian multiculturalism from its inception in 1971 to its current tendencies and determine whether this policy is still attainable by referring to significant views of Hall, Taylor, Duchastel, Perin, Clifford, Drache, Hoyos and Kymlicka. These theoretical insights are explored in the case of the Serbian diaspora in Canada. The study is based on the oral histories of the members of the first generation of Serbian immigrants to Canada, conducted in July 2008 in Toronto. Bennett’s Developmental Model of Intercultural Sensitivity is used as a theoretical framework. The results show that the first generation of Serbian immigrants shares stronger ties with the mother country than their descendants; however, respect for the values of diversity and hybridity contributes to the process of making inter-generational differences less conspicuous which, regarding the Serbian diasporic community, represents a proof of the topicality of the Canadian multicultural experiment.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.115
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0220.007
Scholarly communication0.0070.001
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.285
Teacher spread0.245 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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