Refugee Youth and Transition to Further Education, Training, and Employment in Australia: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Young people with refugee experiences are widely acknowledged as encountering multiple disadvantages that affect their school completion and retention, university entry, and subsequent employment. This paper discusses the rationale for and protocol of a mixed methods investigation focusing on improving education and employment outcomes among refugee background youth aged 15 to 24 years from three focus regions: the Middle East (Afghanistan, Iran, Iraq, Syria), South Asia (Nepal, Bhutan, Myanmar/Burma, Pakistan) and Africa (Sudan, South Sudan, Liberia, Ethiopia, Somalia, DR Congo). OBJECTIVE: The rationale of the project is to identify the facilitators and barriers to successful transition from school to further education and employment; investigate participant awareness of support systems available when faced with education and employment difficulties; redress the disadvantages encountered by refugee background youth; and bridge the gap between research, policy, and practice in relation to social inclusion and participation. METHODS: The study involves collecting survey data from 600 youth followed by individual interviews with a subset of 60 youth, their parents/primary caregivers, and their teachers. A cross-sectional survey will assess facilitators and barriers to successful transition from school to further education and employment. Individual interviews will provide context-rich data on key issues relevant to education and employment outcomes. RESULTS: The study began in 2016 and is due for completion by the end of 2019. The quantitative survey has been conducted with 635 participants and was closed in March 2019. The qualitative interview stage is ongoing, and the current total in April 2019 is 93 participants including educators, youth, and family members of the youth. Analysis and presentation of results will be available in 2020. Some preliminary findings will be available during the late half of 2019. CONCLUSIONS: This project will contribute new and unique insights to knowledge in relation to key factors influencing education and employment outcomes among refugee youth. This research will enable effective planning for the needs of some of Australia's most disadvantaged and marginalized young people, leading to a sustainable improvement in the education and employability of young refugees. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12632.
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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 | 0.085 | 0.062 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 0.010 |
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".