The educational attainment of Aboriginal peoples in Canada : an analysis of the 2001 Aboriginal Peoples Survey (APS)
Bibliographic record
Abstract
Educational inequality is experienced by Aboriginal peoples and is long-standing.On average, the educational attainment of Aboriginal peoples is significantly lower than for non-Aboriginal people.As a result, there is a large gap between Aboriginaland non- Aboriginal people at every level of educational attainment.Despite efforts to address this inequality, obstacles continue to prevent Aboriginal peoples from completing secondary school and achieving higher levels of schooling.Academics and policy makers have failed to uncover the causes of educational inequality despite decades of effort and observation.This thesis addresses this gap by using the 200l Aboriginal Peoples Survey to identify the factors contributing to the educational attainment of Aboriginal peoples in Canada.The results of this study find that receiving financial assistance for post- secondary education is the single most important factor contributing to educational attainment.Surprisingly, the majority of Aboriginal students with treaty status who are entitled to funding for post-secondary education do not receive iU a breach of the governments'treaty obligations.There are also non-Status Aboriginal peoples who would benefit from greater access to funding outside of treaty obligations.This study also reveals that educational attainment is unequally distributed among Aboriginal peoples.Women and those without treaty status have the highest educational attainment.This research illustrates the need for increased funding for post-secondary education for all Aboriginal students, and initiatives to improve secondary school completion rates.also like to acknowledge the assistance of Dr. Andrew Woolford and Dr. Sandra Kouritzin, members of my advisory committee who have also helped me improve this research, I would also like to recognize the respondents of the 2001 Aboriginal Peoples Survey.Their participation, time devoted, and provision of personal information is appreciated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".