What kind of learning? For what purpose? Reflections on a critical adult education approach to online Social Work and Education courses serving Indigenous distance learners
Bibliographic record
Abstract
This article begins with a critical examination of adult education theory and practice and its engagement (or lack) with Indigenous knowledges and communities. In doing so, the article reveals the contradictions of early citizenry adult education that sought to bring educational programs to the people without a critical examination of the western hegemonic orientation of such programming. The critique then moves to a discussion of transformative learning within adult education emerging in the late 1970s. In tracing the evolution of adult education theory and practice, the critique asks the questions: “Access to what kind of adult education?, and” “For what purposes?” The article then moves to the present and explores contemporary distance education, with an emphasis on online learning that may be aimed at Indigenous adult learners. In particular, the article explores the possibilities of online distance learning to not only bring educational programming to Indigenous communities and thereby building upon the social justice imperative of accessibility, but also to design decolonizing curricula that engages Indigenous knowledges and upholds oral culture.
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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.048 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.010 |
| 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".