Bibliographic record
Abstract
In Canada, there are three groups of Aboriginal people, also referred to as Indigenous peoples, and these include the First Nations, Inuit, and Métis. Although often thought of collectively, each has its distinct history, culture, and perspectives. The Métis people are mixed-culture people stemming from a long history of Indigenous people and European settlers intermixing and having offspring. Furthermore, the living history representing mixed ancestry and family heritage is often ignored, specifically within higher education. Dominant narratives permeate the curriculum across all levels of education, further marginalizing the stories of Métis people. I explore the experiences of Métis women in higher education within a specific region in Canada. Using semi-structured interview questions and written narratives, I examine the concepts of identity, institutional practices, and reconciliation as described by Métis women. Results assist in providing a voice to the Métis women’s experiences as they challenge and resist colonial narratives of their culture and expand upon a new vision of Métis content inclusion in higher education as reconciliation.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.058 | 0.018 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".