Ketmite'tmnej: Remember who you are. The educational histories of three generations of Mi'kmaq women
Bibliographic record
Abstract
Motivating Aboriginal youth to complete their education is of great importance, not only to the future of Aboriginal communities, but to the whole of Canadian society. When we come to understand present-day Mi'kmaq customs, beliefs, values, and attitudes as they may relate to education, we will be able to proceed with increased awareness for all involved in the education of Mi'kmaq youth. Focusing on one of Prince Edward Island's First Nation Reserves where all students attend public schools, this site specific research investigates the presence of Mi'kmaq cultural traditions and how they may impact on the academic achievement of Mi'kmaq youth. Ethnographic style interviewing to explore the educational histories of four Mi'kmaq women in one family, through three different generations, yields insights about Mi'kmaq culture, spirituality, and traditions. The voices of all four Mi'kmaq women are woven around the thoughts of other researchers in an attempt to promote cross-cultural communication and understanding. Themes emerging from the research include the internal and external forces which challenge the identity of Aboriginal people, the characteristics of a school environment which supports learning for Aboriginal students, and an examination of the cultural/spiritual reasons underlying academic success for Aboriginal learners.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".