Acquiring intercultural competencies through language learning and its potential impact on immigration integration in the province of Ontario, Canada
Bibliographic record
Abstract
This thesis explores the concept of intercultural competencies and their impact on migrants’ social integration and integration into the labour force in the Ontario province, Canada. The literature review explores fundamental perspectives on the concept of intercultural competencies and the framework of intercultural competencies. It also discusses intercultural competency development and acquisition methods at educational institutions, especially through language learning. Various approaches to acculturation are reviewed and analyzed. The second part of the literature review focuses on the cultivation of intercultural competencies within the Canadian context. It investigates the concept of migration and its fundamental types while also analyzing the support mechanisms available for immigrants in Canada and Ontario province specifically. The empirical research allows us to build the connection between the awareness of intercultural competencies and their impact on migrants and their integration into the host society. Findings show that possessing intercultural competencies promotes higher rates of successful integration, acculturation, sociocultural and psychological adaptation, and professional integration. Recommendations include the promotion of fostering intercultural competencies in migrants through educational institutions. The outcomes of this research will be of practical value to those studying immigrants' social and cultural adaptation in a new country.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".