Parrhesia ‘From the Heart’: Decolonial disruption in K-12 schools
Bibliographic record
Abstract
On October 14th, 2023, over 70% of Australians rejected the government’s referendum to include Indigenous peoples in the constitution and establish an Indigenous voice in parliament. We locate the latest Australian rejection as another episode in a continuing global project of Indigenous dispossession and a flash point to escalating critical Indigenous activism in K-12 schools. This paper centres on learning through suppressed Indigenous histories and voices by positioning Foucault’s notion of parrhesia (truth-telling) as decolonial defiance. We present three qualitative themes to guide teachers to perform this activist-centred work: 1). Founding Respect, 2). Humble Leadership, & 3). Indigenous Representation - drawn from the Weaving Stories of Strength (WSS) project. WSS conducted yarning sessions, an Indigenous dialogic method, with sixteen Indigenous educational experts from the United States, Canada, New Zealand and Australia. Synthesising their voices, we outline the conditions necessary to mobilise parrhesia as decolonial strategies.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.037 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.015 |
| 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".