Bibliographic record
Abstract
Aboriginal people in Alice Springs mapped the safe places in their Town Camps. This participatory research led to the implementation of safety features. Safety mapping was developed in response to deficit-based research which pathologized Aboriginal people in Alice Springs. Safety mapping was conducted with Aboriginal people in Town Camps to identify safe places and improve safety. A strengths-based approach showed that problems and their solutions are known, and there are considerable safety assets within Town Camps. The safety mapping centred the voices and experiences of Aboriginal people to produce research that was of benefit to Town Campers, over which Indigenous people retained ownership. This paper highlights that an Indigenist approach to participatory action research is strengthened by Indigenous knowledge in driving social justice.
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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 | 0.061 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.016 | 0.051 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".