The University of Ottawa Indigenous Peoples Education Curriculum Model: Basis in the Development of Indigenous Peoples Education Curriculum for PNU-North Luzon
Bibliographic record
Abstract
The study investigated and analyzed the Aboriginal Teacher Education Program (ATEP), Faculty of Education, University of Ottawa as basis in the development of indigenous peoples education curriculum for the Philippine Normal University-North Luzon, the indigenous peoples education hub. Data gathering procedure included document analysis, surve,y and interview. The respondents included the director, assistant director of teacher education, six faculty and one alumna of the University of Ottawa, Ontario, Canada. The conceptual framework is anchored on active, collaborative inquiry of reflective practice. The ATEP is both campus and community-based. A variety of assessment techniques were used in evaluating the program. The program reflects researches in teacher education and ethical standards of teaching profession of Ontario. ATEP courses have fewer contact hours than baccalaureate education program. Ontario College of Teachers certify ATEP graduates to teach in primary, junior to Grade 6. Moreover, graduates receive greater career opportunities nationally and abroad. Integration of indigenous knowledge and issues during instruction depends much on the professor. Other universities in Canada are more grounded and focused on indigenous education and have better enrolment in aboriginal teacher education program than the University of Ottawa.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".