Aboriginal Student Persistence and Success in Ontario Colleges
Bibliographic record
Abstract
This study relies on a mixed method research approach with a focus on qualitative research including open-ended, semi-structured interviews at Aboriginal Resource Centres in three colleges in Ontario. Interviews were conducted with 31 participants engaged with Aboriginal Resource Centres, including Aboriginal students, staff and Elders. Participants spoke about their interactions with the Ontario college system including their positive and negative experiences. The research process is also informed by an in-depth analysis of various studies and reports regarding Aboriginal peoples, education and enrolment statistics from the 24 Ontario colleges. The overall data analysis and interpretation includes insight from all of these data sources. The research is guided by a two-eyed seeing approach (Iwama, Marshall, Marshall, Barlett, 2009) that respects a combination of Western and Aboriginal worldviews; however, a concerted effort has been made to honour Indigenous paradigms thus, at times, this minimizes the inclusion of traditional Euro-centric views and methodology. Nevertheless, parallels were drawn between Euro-centric student development and engagement theories and Indigenous paradigms to provide insight into how postsecondary institutions can support Aboriginal students and create a safe and welcoming environment on campus for all Aboriginal peoples. An Ojibwe Anishinabe Elder recognized by her community provided guidance throughout the research process. She allies with students connecting them to traditional protocols and shares authentic Indigenous teachings. Further, to respect the place of Aboriginal voices, a collection of Elder reflections describes a vision for Aboriginal education, and specifically postsecondary education.The conclusions drawn from the study suggest that many colleges in Canada, and Ontario, are helping Aboriginal students obtain a postsecondary credential. Colleges are creating a supportive and welcoming environment and Aboriginal Resource Centres are helping students connect with their communities, institutions and Aboriginal cultures. In spite of this success, many Aboriginal students do not reach postsecondary education. Many Aboriginal students are not engaging with these centres and Aboriginal peoples continue to experience racism on campus. The findings indicate that true collaboration and meaningful consultation with Aboriginal communities is needed to "Indigenize" the campuses.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 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".