Tensions between policy and practice : reconciliation agendas in the Australian curriculum English
Bibliographic record
Abstract
ABSTRACT: In various parts of the world, Indigenous and non-Indigenous peoples are actively working towards Reconciliation. In Australia, the context in which we each undertake our work as educationalists and researchers, the Reconciliation agenda has been pushed into schools and English teachers have been called on to share responsibility for facilitating the move towards a new national order. The recently introduced Australian Curriculum mandates that Aboriginal and Torres Strait Islander Histories and Cultures be embedded with “a strong ” but “varying presence ” into each learning area (Australian Curriculum, Assessment and Reporting Authority, 2013). In this paper we consider the tensions between policy and practice, when discourses external to education are recontextualised into the discipline of English. We do so by applying an analytical framework based on Bernstein’s (1990, 1996, 2000) sociological theories about the structure of instructional and regulative discourses. Our findings suggest that the space to exert Reconciliatory agendas in the Australian Curriculum English is ambiguous and thus holds the potential to not only marginalise Indigenous knowledges but also to create tensions between policy and practice for non-Indigenous teachers of English.
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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 | 0.052 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.020 | 0.069 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".