Potential Role of the Growth and Empowerment Measure to Enhance Environmental Health Research and Interventions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The often-overlooked ability to protect and restore lost psychosocial wellbeing and mental health in the face of increasing environmental stress, dwindling capacity to meet basic needs and climate change is arguably one of our greatest health challenges. Poor mental health is already a leading contributor to the global burden of disability and reduces human capacity for collective planning and innovating, responding to crises and recovering from disasters and losses. Multiple environmental distresses, from water and food insecurity to climate change, place enormous pressure on people’s ability to feel in control, see meaning and purposes in their lives and stay connected to one another in increasingly desperate circumstances.This situation is familiar to Aboriginal Australians, who have endured systematic disempowerment of their culture and families and dispossession of their Lands, waters and governance by Europeans since 1788. Although huge health inequalities remain between Aboriginal and non-Indigenous Australians, Aboriginal people have made remarkable contributions to Australian society and health research – especially towards understanding healing and empowerment.This presentation will argue the relevance of empowerment to address global and local environmental health challenges. We will introduce the Australian Aboriginal-informed tool, the Growth and Empowerment Measure [GEM], which measures complex psychosocial domains, e.g. identity, healing from painful feelings, creating safety, self-efficacy, voice, spirituality and community strength. Confirmatory Factor Analysis has demonstrated GEM’s cross-cultural validity and measurement invariance (Indigenous and non-Indigenous). We will discuss its potential contribution to environmental epidemiology, eg identifying community empowerment needs, health impact assessment (especially of developments that threaten fundamental environmental values) and evaluation of environmental health interventions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it