Beyond “Indigenous Social Work” and Toward Decolonial Possibility: Stories from Toronto’s Red Road
Bibliographic record
Abstract
While social work has been a specific technology of settler colonialism levied against Indigenous Peoples, the phenomenon of “Indigenous social work” is now rather comfortably discussed and included within university curricula and places of social work practice. This article is a creative adaptation of a research project with four generations of Indigenous social workers in Toronto, culminating in 10 intersecting short stories that work to make visible “the Good Red Road” in the city. The story landmark shared here is one of these stories, a pit stop along the road. Its function exists somewhere between that of petroglyphs, and carving your name into wet cement. It helps mark where we have been as Indigenous social workers, how we imprint onto the landscape, and how the Land can guide us in important directions. This landmark is an invitation for those involved in Indigenous social work to not only consider the story pathways we have created, but how these story landmarks could lead Indigenous Peoples, communities, and Nations to destinations previously foreclosed to our imaginaries by the boundaries of our professional survival. That what may lay between us and decolonial possibilities, is our refusal of the profession itself.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.050 | 0.035 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".