isihcikêwinihk kâkî nâtawihon: Healing Through Ceremony
Bibliographic record
Abstract
isihcikêwinihk kâkî nâtawihon (Healing through Ceremony) is an audio-visual learning experience created in ceremony and in relationship with knowledge-keepers, wisdom-holders, language speakers, and the survivors of Indian Residential Schools and their descendants. In ceremony and in language, the authors met with 23 knowledge-keepers and Indigenous community members who shared their experiences of “healing through ceremony.” Through protocol and relationship, the knowledge-keepers and Indigenous community members gave permission to the authors to have the teachings and stories recorded and documented. The audio-visual learning experience came to be understood as an experience of kiskinowapahtam – to heal, teach, and learn by watching and doing. The teachings and stories shared in isihcikêwinihk kâkî nâtawihon guide social workers toward understanding how to support Indigenous communities in healing from the legacy of Residential Schools and the lasting intergenerational impacts of colonization. isihcikêwinihk kâkî nâtawihon supports the preservation of Indigenous knowledge regarding healing and ceremony and directly impacts current and future generations through providing this knowledge to social workers serving Indigenous communities. From this teaching experience, the knowledge-keepers, community members, and authors share a collective vision that Indigenous children, families, and communities encounter social workers who understand, honour, and trust the healing that happens in ceremony.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".