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Record W7017893406

The Choice of Acculturation Strategies: Intercultural Adaptation of International Students from Sub-Saharan African Francophone Countries in Ontario

2020· other· en· W7017893406 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2020
Typeother
Languageen
FieldMedicine
TopicArtificial Intelligence in Healthcare and Education
Canadian institutionsnot available
Fundersnot available
KeywordsAcculturationIntercultural competenceCitizenshipImmigrationFrenchStudy abroadCultural competenceHigher educationCompetence (human resources)International education
DOInot available

Abstract

fetched live from OpenAlex

According to Immigration, Refugees and Citizenship Canada (2019), the number of foreign students studying in Canadian public colleges and universities rose 16.25% in 2018 for an overall increase of 73% in the five years since 2014. The number of international students aspiring to obtain a degree in Canadian higher education institutions has been increasingly growing. Yet, attending post-secondary institutions in a culture different from ones own may result in challenges of cross-cultural adaptations. Black-African international students are not different in this regard. Based on a mixed methods research, the study draws from Berrys (1997) fourfold acculturation theory, Kims (1988) integrative communication theory and LaFramboise et al. (1993) bicultural competence model to investigate the international students from Sub-Saharan African francophone countries choice of acculturation strategies as well as their overall intercultural adaptation in bilingual post-secondary institutions in Ontario. Results from the quantitative analysis revealed assimilation as preferred acculturation mode while qualitative analysis identified both integration and separation as preferred strategies. The participants reported support from academic staff but also a significant lack of information, and difficulties adapting to the teaching style.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.050
GPT teacher head0.262
Teacher spread0.212 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueYork University Digital Library (York University)Same topicArtificial Intelligence in Healthcare and EducationFrench-language works237,207