Neither this nor that: the challenge of social justice for non-indigenous English teachers in First Nations Australian education contexts
Bibliographic record
Abstract
This article examines and critiques gap-based education policies that are based on statistical and reductive conceptualisations of success for First Nations students in Australia. The policy desire to achieve social justice underpinned by parity of outcomes across a range of life indicators (including standardised English literacy) between First Nations Australians and non-Indigenous Australians is embedded in programmatic approaches to pedagogy such as Accelerated Literacy (AL). We examine the experiences of Bruce, a teacher teaching English in the middle years of school in a school that mandated AL as a whole-of-school approach to English and literacy instruction. We show how intersecting notions of social justice can collide in the English classroom and how teachers in these contexts are in danger of re-colonising through English teaching practices that neither produce statistical improvement nor advance culturally responsive teaching based on giving primacy to Indigenous-authored texts in subject 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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.021 | 0.051 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| 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".