Strength and uniqueness - the ripple effect of the BBM Health Justice Partnership sharing of knowledge and increasing empowerment: second research and impact evaluation report of a Health Justice Partnership – Bagaraybang bagaraybang mayinygalang (BBM): Empowering & Alleviating: A Health Justice Partnership (HJP) of the Hume Riverina Community Legal Service (HRCLS) & Albury Wodonga Aboriginal Health Service (AWAHS) offering legal support for social & emotional well-being with Aboriginal Peoples in Northeast NSW and Victoria
Bibliographic record
Abstract
This report, entitled Strength and uniqueness - the ripple effect of the BBM Health Justice Partnership sharing of knowledge and increasing empowerment: second research and impact evaluation report’s, key concern is with the data collected in 2024 from April 2023- March 2024 and key learnings, progression, achievements, and areas for action as well as findings and conclusions. The report examines the sustainable development goals including issues around inequality, health and wellbeing, poverty and justice. These shape and inform the recommendations for this second report. The overarching question for this research is to test if the BBM Program is effective and impactful in Empowering & Alleviating Aboriginal community outcomes through its Health Justice Partnership (HJP) by offering legal support for social & emotional well-being between the Hume Riverina Community Legal Service (HRCLS) & Albury Wodonga Aboriginal Health Service (AWAHS). \n \nA further question explores what the lessons are, to support other Integrated Service Programs and HJPs models that are envisaged, in start-up phase, are underway and other lessons for improved legal service delivery to ensure reach, engagement, capability, empowerment and collaboration to improve access to justice and social determinant of health outcomes to address inequality so often entrenched in systems that impede access to equality before the law and desirable human rights outcomes in the lives of those who are the most disadvantaged
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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 | 0.079 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".