What Explains the Educational Attainment Gap between Aboriginal and Non-Aboriginal Youth?
Bibliographic record
Abstract
Aboriginal people generally have lower levels of educational attainment than other groups in Canada, but little is known about the reasons behind this gap. This study is the second of two by the same author investigating the issue in detail. The first paper (Frenette 2011) concludes that the labour market benefits to pursuing further schooling are generally not lower for Aboriginal people than for non-Aboriginal people. This second paper takes a more direct approach to the subject by examining the gap in educational attainment between Aboriginal and non-Aboriginal youth using the Youth in Transition Survey (YITS), Cohort A. Aboriginal people who live on-reserve or in the North are excluded from the YITS and, thus, from this analysis. The results of the analysis show that most (90 percent) of the university attendance gap among high school graduates is associated with differences in relevant academic and socio-economic characteristics. The largest contributing factor among these is academic performance (especially differences in performance on scholastic, as opposed to standardized, tests). Differences in parental income account for very little of the university attendance gap, even when academic factors are excluded from the models (and thus do not absorb part of the indirect effect of income). Differences in academic and socio-economic characteristics explain a smaller proportion of the gap in high school completion than in university attendance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".