Surviving to thriving: post-secondary education for refugee youth in smaller centres in Canada
Bibliographic record
Abstract
The research investigates refugee youth’s aspirations for and access to post-secondary education in St. John’s, Newfoundland and Labrador, Canada. The theoretical framework that underpins this study consists of segmented assimilation theory and the bioecological model of human development. A basic qualitative research approach was employed. Twenty refugee youths and three staff members from educational service providers participated in this study. Data were collected through one-on-one semi-structured interviews. Findings revealed that new life in Canada instilled hope into refugee youth as they aspired to get into university after high school. Refugee youth referred to their parents, support teachers and staff in high school, their friends, and university academic advisors as important people who helped them realize their educational goals. In addition, three educational programs were identified by refugee youth as helpful in preparing them for post-secondary education. Nonetheless, refugee youth’s access to post-secondary education was impeded by a number of barriers, including financial difficulties resulting from the repayment of transportation loans and a lack of target scholarships for refugee students pursuing post-secondary education, lack of information about post-secondary admission requirements, scholarships, and on-campus employment opportunities, negative peer influence from refugee students who were less motivated, limited communication with local peers, and fear of the unknown and the academic challenges they would face in post-secondary education. In addition, refugee youth aged 19 or over found it difficult to further their education due to the policy of high school age limits and a lack of appropriate adult educational programs geared to their needs. Recommendations were also offered to reduce these barriers such as eliminating transportation loans and offering targeted scholarships and bursaries to refugee youth; providing refugee youth with information and assistance they need to make informed decisions about their education and career; increasing the number of ESL teachers at the secondary level and continuing to offer ESL support for college and university refugee students; and optimizing language and academic support for refugee young adults with goals of pursuing post-secondary education.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".