Deadly Dads Support Society: understanding the development and impact of a culturally centred, group-led support strategy for nêhiyaw (Plains Cree) fathers and men
Bibliographic record
Abstract
Through a long-standing community-university partnership, we developed a culturally centred, group-led support strategy for nêhiyaw (Plains Cree) fathers and men to enhance their well-being. A community-based participatory research approach was adapted to honour nêhiyaw ways of knowing. Group-led and developed support activities for fathers and men took place from August 2021 to January 2023, with data gathered from Wisdom Circles, meeting minutes, reflexive journals, photos, implementation notes, and community reports. Data analysis was narrative, relational, and non-linear. Knowledge sharing efforts aimed to: 1) explore lessons from co-developing support activities; 2) understand the significance of gathering in safe and healthy ways; and 3) examine the impacts of support on members. The group's development was rooted in mutual generosity and overcoming institutional inequities to offer meaningful supports. This resulted in healthy ways of gathering and supporting one another through relational connections; learning from and identifying with one another; and breaking cycles of intergenerational trauma through cultural connections, sharing, and expressions of love. Experiential and pressure-free activities contributed to a sense of belonging, positivity, and collective ownership, and supported participants through life difficulties. The success and sustainability of the group relied on transcending Western academic approaches to embrace community ways of knowing and relationality.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".