Emancipatory decoloniality as leadership in social service organizations: Insights from indigenous and anti-oppressive yarnings
Bibliographic record
Abstract
Abstract Around the globe, there is a growing demand for leadership in resolving longstanding social injustices experienced by Indigenous peoples. As part of a larger, international study, this article draws on early findings from yarnings/qualitative interviews to contribute to theorizing Indigenous leadership in social service organizations. Within our research design, the team of Indigenous and non-Indigenous researchers consciously centre Indigenous ways of knowing, being, and doing to build emancipatory, decolonizing theory and practice. The analysis in this article identifies Indigenous social justice leadership in several overlapping forms, including Indigenous-centred/cultural-centred ways of knowing, being, and doing; intersectional identities; partnerships; and envisioning for all. The article concludes with further early theorizing and calls for future research to delve more deeply into Indigenous leadership as it develops in resistance to new conditions, including the far-right push-back against human rights and equity and the constraints of neoliberalism.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.035 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.004 |
| 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".