Tracing spectres of whiteness: discourse and the construction of teaching subjects in urban Aboriginal education
Bibliographic record
Abstract
The author traces how discourse functions in the context of a school-based, urban Aboriginal education initiative, with a focus on the construction and organization of teaching subjects. Critical discourse analysis that traces spectres reveals some of the ways that whiteness and Eurocentrism create the possibilities for, and the conditions in which teachers take up, the positions: victim of racism, arbiter of authenticity, and rescuer. Consideration of the multiple, complex, and shifting positions teachers occupy within whiteness in general, and in colonial systems of education in particular, offers unique possibilities when untangling and reconfiguring teachers' constructions of Aboriginality/Indigeneity and responses to Aboriginal/Indigenous education. This theory building also contributes to the larger field of curriculum studies by demonstrating how consideration of ‘unheroic tales’ can aid in theorizing teacher identity and difference, both within and beyond the markers Indigenous/non-Indigenous.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.019 | 0.064 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 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".