“And they are still the guardians of these sacred waters …”: Land as a process of reconciliation.
Bibliographic record
Abstract
Given that Indigenous Peoples in Canada continue to face health disparities as a result of ongoing colonial attempts at genocide, reconciliation requires using a decolonized health framework that identifies oppression and marginalization while seeking to improve Indigenous Peoples' health and facilitates a shared understanding of well-being. Community and land-based interventions hold promise in providing insight into how the reconciliatory process can occur and have been shown to successfully address the health disparities experienced by Indigenous Peoples by connecting participants to their kin, culture, and identity. However, the impact of these interventions on facilitators, both Indigenous and non-Indigenous, is lesser known. This qualitative study explores the reconciliatory effects of a decolonized framework on 10 Indigenous and ally community-engaged facilitators during a land-based healing lodge using semistructured pre- and postinterviews. Findings indicate that engaging with the land as an equitable research partner while being reflective allows facilitators to develop a decolonized relationship with the place an intervention is being held, themselves, and effectively engage with the partner community. Furthermore, by implementing a decolonized approach to culturally centered interventions, several facilitators' perspectives of healing transitioned from understanding healing as an outcome to a holistic process that engages place and the broader ecology. These findings signal a need for those working toward reconciliation (e.g., researchers, evaluators, health and health-allied professionals) to consider the influence of Indigenous ways of knowing and being on both Indigenous and non-Indigenous individuals involved in the healing process. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.059 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| 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".