Potential Role of the Growth and Empowerment Measure to Enhance Environmental Health Research and Interventions
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.083 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".