The Sisyphean continuum: countering the racial-colonial challenges of Indigenous education
Bibliographic record
Abstract
Using the symbolism of what we consider to be a ‘Sisyphean continuum’, in this paper the Anglosphere countries of Canada, New Zealand, the United States, and Australia are grouped to strategically reveal the shared challenges Indigenous peoples encounter in racial-colonial education systems. Fittingly, parallels are drawn between the punitive loop the mythical figure Sisyphus was doomed to. For Indigenous peoples bound up in dominant educational spaces, the barrage of racial-colonial institutional tools and mechanisms, enduring racism and cultural assimilation, the absence of collective achievement, the lack of Indigenous representation (e.g. personnel or knowledge), in parallel with sustained inter-generational advocacy, aptly mirrors the exhaustive punitive loop of Sisyphus. Guided by theoretical bridges synergising Indigenous and Western qualitative research techniques, three commonly repeated challenges (1. Deficit thinking; 2. Institutions; 3. Curriculum) are the focus of this paper. These themes are drawn from a broader study that sought the wisdom of sixteen Indigenous experts from across the Anglosphere. Our paper’s findings recentre the cycling educational challenges Indigenous peoples encounter and draw attention to the urgent need to turn towards and embrace marginalised voices and knowledge paradigms.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.047 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".