A Comparison of Adjustment to University between Immigrant and Non-Immigrant Students
Bibliographic record
Abstract
Due to large immigrant student numbers enrolled in post-secondary education in Canada, adjustment of immigrant youth to mainstream culture at the university level is an important issue for Canadian educators.However, research on immigrant students' adjustment while attending Canadian educational institutions is scarce.The purpose of the present thesis was to address this gap by examining Canadian immigrant students' adjustment to university and to identify potential protective factors that predict immigrant students' successful adjustment.The adjustment of immigrant students to university was examined by comparing immigrant and Canadian-born students on attachment to university and academic, social and emotional adjustment to university using the Student Adjustment to College Questionnaire (SACQ).Participants were 75 students from two Canadian universities.Results showed that Canadian-born students scored higher in attachment to university than foreign-born students, but did not differ on the other adjustment scales.There were similarities and differences between the two groups in how family demographic and relationship variables related to university adjustment.Neither age at arrival nor years in Canada were found to relate to university adjustment in the immigrant group.While raising new questions, the present study contributes to existing research on the adaptation of foreign-born youth to the host culture as well as to findings on students' adjustment to university.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".