The role of post-secondary education in health and well-being through employment among under-represented youths in OECD countries
Bibliographic record
Abstract
Post-secondary education is a critical determinant of economic competitiveness, labour market success, and financial stability, all of which significantly impact lifelong health and well-being (Goldman & Smith, 2011; Olshansky et al., 2012). However, systemic discrimination and structural barriers, such as institutional racism within educational systems, hinder access to and success in post-secondary education for marginalized groups (Shankar et al., 2013). These obstacles restrict their career advancements and economic mobility, exacerbating health inequities among them (Braveman et al., 2011). Within Organization for Economic Cooperation and Development (OECD) countries, research demonstrates that higher levels of education are associated with improved employment prospects and higher earnings (OECD, 2024). However, despite these well-established benefits, under-represented youth such as Black, Indigenous, low-income, disabled and foreign-born students are less likely to attain upper secondary education compared to their peers and remain underrepresented in post-secondary institutions (James & Turner, 2017; OECD, 2024; Porter & Ph, 2024; Robson et al., 2014, 2016; Showunmi, 2023). Given the systemic barriers to educational and career success among under-represented youth, their disproportionate representation in post-secondary institutions, and in turn, their adverse health outcomes, there is an urgent need to understand the complex interplay between education, employment, and health among them. This is particularly the case for youth who live at the intersections of multiple sites of oppression within the Canadian context, including African, Caribbean and Black youth (Watson-Singleton et al., 2023). Furthermore, identifying the barriers and facilitators to post-secondary education is essential for developing strategies that advance educational equity, support lifelong socio-economic mobility, and improve health for these groups across the life course. Primary question What are the relationships between post-secondary education, employment (e.g., economic and labour market success, financial stability), and health among under-represented youth? This review will focus on two pathways: 1) the direct impact of post-secondary education on health, and 2) the indirect impact of post-secondary education on health through employment. Secondary question What are the barriers and facilitators to post-secondary education among under-represented youth?
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".