INDIGEGOGY A Transformative Indigenous Educational Process
Bibliographic record
Abstract
Social work training programs have not been able to keep step with the needs of Indigenous people since the advent of the profession. As former agents of government assimilation, social workers now find themselves in difficult positions where they are unable to help Indigenous people, despite their best intentions. Indigenous Social Work Education has become a necessary response to the growing needs of Indigenous people, and increasing social problems in Canada. Furthermore, Indigenous people who practice Indigenous social work have become vital to the survival of Indigenous people and their communities. The teaching and practice of Indigenized, social work education has become a strong presence in the reclamation of indigenous identity. A decolonized peda- gogy such as the one presented in the case study of the Aboriginal Field of Study (AFS) at Wilfrid Laurier University (WLU) affirms indigenous ways of being, knowing, and doing and places control and ownership of helping practices firmly in the hands of Indigenous people. The case study outlines four critical elements of the AFS: Elder-in-Residence, Circle Pedagogy, Wholistic Evaluation and Culture Camp that are used to guide Master of Social Work (MSW) students on how to develop a Wholistic Healing Practice framework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.027 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".