Bibliographic record
Abstract
No more kiyams7' Metis women break the silence of child sexual abuse, is a glimpse into the lives of four MCtis women who were raised in an Aboriginal community and who speak to the effects and the obstacles of trying to heal fiom an abuse that affects not only them, but also their families and communities. As Metis people, the women in this thesis bring to light, the generational abuses that affect the healing process. They give a picture of how healing is a very personal journey but at the same time a collective process. Rose, Betsy, Angela and Rena provide us with insight into why healing from child sexual abuse needs to address a cultural perspective. Rose became a victim of a respected elderly uncle. Betsy and Angela's fathers were their abusers. For Rena it was her stepfather, grandfather, and cousins; how does one send all those significant people to jail? In addition, remain a 'part' of family and community. The M6tis are raised to be very proud and loyal to family and community. We do not heal alone. This work is about honouring individual strength and gifts in order to heal. It speaks to healing that is not in isolation from identity as a Metis or in isolation from one's community. This thesis is about acknowledging the strengths of MCtis women by giving voice to their stories, their dreams, and their lives.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".