Empowerment and the ecological determinants of health: three critical capacities for practitioners
Bibliographic record
Abstract
Human agency or the expression of intentionality towards some form of betterment has long occupied human imagination and creativity. The ways in which we express such aspirations are fundamentally informed by our beliefs about the nature of reality, meanings of human well-being and progress, and the ways in which our social locations shape our interests. Within Western health-promoting discourse and practice, such processes have largely been expressed through the construct of empowerment. To date, like health, much empowerment practice has been implicitly rooted in Cartesianism, has tended towards anthropocentrism and in cases where it has engaged with environmental issues, has mirrored environmentalism's focus on externalities and objectivity. These tendencies coupled with the increasing complexity of global, ecological, human well-being issues call empowerment practitioners to integrate new kinds of capacities more suited to addressing the ecological determinants of health. Drawing in part on the author's empowerment research over more than a decade, this article distinguishes between a range of epistemological perspectives underlying contemporary empowerment practices while fore-grounding the concepts of place-based agency and social-ecological resilience. These constructs in turn form the basis for three capacities considered critical for practitioners addressing human-ecological well-being.
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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 | 0.036 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.176 |
| Scholarly communication | 0.019 | 0.024 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.010 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 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".