Resonating opinions and identities: Using poetics methods to explore non-Aboriginal attitudes towards Aboriginal reconciliation in Australia
Bibliographic record
Abstract
This article reports findings from an ongoing research project into non-Aboriginal attitudes towards Aboriginal reconciliation in Australia and Canada. The two countries share important details in their histories of mistreatment of Indigenous peoples as well as in their postcolonial attempts at reconciliation. Our research uses focus groups and an expressly poetic framework of analysis to explore quotidian or “less public” discourses about Aboriginal reconciliation in both countries. The public poetics approach used here lends itself to simultaneous exploration of both referential and textural elements of participant discourses within the focus groups. This leads to the finding that non-Aboriginal people in both countries conceive of aboriginal reconciliation as a highly transactional phenomenon – whose leading parties are a non-Indigenous “us” and an Indigenous “them” in each case.
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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 | 0.022 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.012 |
| 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".