Barriers Faced by Canadian Aboriginal Adults as They Return To Postsecondary School
Bibliographic record
Abstract
Aboriginal people in Canada are less likely to complete postsecondary education than are non-Aboriginal people. This lack of education leads to increased rates of unemployment and poverty and the need for additional government supports. The purpose of this project study was to identify and examine barriers faced by Canadian Aboriginal adult students as they return to school for postsecondary education. The conceptual framework for this qualitative study was based on the work of Ertmer, which suggests barriers can be placed into broad categories of extrinsic and intrinsic barriers. A case study design was used with a purposeful sample from a local academic institution. Eleven Canadian Aboriginal adult students were interviewed, 6 who successfully completed the college entrance program and 5 who did not complete the program. One counselor from the program was also interviewed to help provide a better understanding of the complexities of the identified barriers. Data analysis included substantive and theoretical coding. Thematic analysis led to 8 overall themes or barriers that affected these students' success: level of self-confidence, social environment, racism, spirituality, government policies, mental health and addictions, perceived value of education, and perceived need to demonstrate leadership. Recommendations include the development of a professional learning community made up of students, teachers, and the Aboriginal communities where the students lived. The project emanating from this study is a 3-part workshop intended to identify and mitigate barriers of Canadian Aboriginal adult students. Understanding and mitigating the barriers will promote positive social change by increasing the success rates of this population of students as they attempt to return to postsecondary 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".