“Mother first, student second”: challenging adversity and balancing identity in the pursuit of university-level education as First Nations mothers in Northeastern Ontario
Bibliographic record
Abstract
The literature surrounding the educational experiences of Indigenous Peoples is an ever-growing and diverse area of research in Canada. However, within this field, the voices of First Nations mothers attending post-secondary needs further development. Through a decolonizing methodology and the use of autoethnography and Indigenous storytelling, this project was designed to explore and better understand our experiences as First Nations student-mothers during the pursuit of university-level education while caring for our children. I argue that Canada’s oppressive history of colonialism and the resulting intergenerational trauma have had specific implications on the post-secondary experiences of the First Nations mothers who participated in this research. The First Nations student- mothers from Laurentian University in Sudbury, Ontario, Canada who contributed to this research tell diverse stories about their experiences however, our narratives intersect in several ways. Areas of interest that emerged from the collected narratives include: (1) how we, as First Nations student-mothers have overcome obstacles, including what difficulties arose for us in the decision to pursue post-secondary education; what motivators contribute to our ongoing success, and how we experience self-doubt and internalized oppression despite our achievements and (2) how we, as First Nations student-mothers have blended our identities as First Nations women, mothers, and students within the university experience. Ultimately, this project aimed to contribute to continued efforts towards decolonization while furthering Indigenous-led research which hopes to improve the educational outlook for future generations of First Nations mothers.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".