Red Dirt Thinking on Power, Pedagogy and Paradigms: Reframing the Dialogue in Remote Education
Bibliographic record
Abstract
Recent debates in Australia, largely led by Aboriginal and Torres Strait Island academics over the past 5 or so years, have focused on the need for non-Indigenous educators to understand how their practices not only demonstrate lack of understanding of Indigenous ways of knowing, being and doing, but even deny their presence. This debate has serious implications for the non-Indigenous remote educator who wishes to support remote students to achieve ‘success’ through their education. The debates on the one hand advocate the decolonising of knowledge, pedagogy and research methods in order to promote more just or equal approaches to research and education, while other voices continue to advocate the pursuit of mainstream dominant Western ‘outcomes’ as the preferred goal for Indigenous students across Australia. This dilemma frames the context for this study. The Remote Education Systems Project, in the Cooperative Research Centre for Remote Economic Participation, seeks to explore these and other questions as part of the broader research agenda being undertaken. This project is particularly focused on large-scale questions such as: ‘What is a remote education for and what would ‘success’ look like in the remote education context?’ We are approaching these research questions from community standpoints and perspectives as a critical starting point for these types of debates and discussions. In doing so, our findings indicate that remote Aboriginal community members have a strong sense of western education and its power to equip young people with critical skills, knowledge and understandings for the future, but also a strong sense of retaining of their ‘own’ knowledge, skills and understanding. This presents a complex challenge for educators who are new to this knowledge interface. Here, we offer the concept of ‘Red Dirt Thinking’ as a new way to position ourselves and engage in situated dialogue about what remote schooling might be if it took into account power issues around Indigenous knowledges in the current policy context. This article questions whether remote communities, schools and systems have, in fact, taken account of the knowledge/power debates that have taken place at an academic level and considers how remote education might consider the implications of stepping outside the ‘Western–Indigenous binary’. It seeks to propose new paradigms that non-Indigenous educators may need to engage in order to de-limit the repositioning of power-laden knowledge and pedagogies offered in remote classrooms.
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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 | 0.042 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.036 | 0.122 |
| Scholarly communication | 0.025 | 0.033 |
| Open science | 0.005 | 0.029 |
| Research integrity | 0.011 | 0.021 |
| Insufficient payload (model declined to judge) | 0.004 | 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".