Building on the Definition of Social and Emotional Wellbeing: An Indigenous (Australian, Canadian, and New Zealand) Viewpoint
Bibliographic record
Abstract
Abstract This article will build on the definition of social and emotional wellbeing (SEWB) used within an Indigenous health framework. We intend to distance it from its current discipline of mental health, the Eurocentric term commonly used in social science literature. This is to emphasize that, within Aboriginal (Rudder and Grant, 2005) and Torres Strait Islander, Maori, and First Nations (Canadian) languages, there is no specific word for “health.” Indigenous peoples from within these countries have a holistic view of health that encompasses the physical, mental, emotional, and environmental spectrum of wellbeing. This article therefore uses “social and emotional wellbeing” rather than the generic Eurocentric terms of “health” or “mental health” to give this a stronger Indigenous voice. The elements of social and emotional wellbeing are discussed from an Indigenous viewpoint and from extracts compiled in work undertaken by Sutherland (2017). The elements explored may offer new perspectives to others. Similarly, this article offers an explanation as to why elements are siloed within the context of mental and physical health. This has led to some parts of SEWB gaining advantages over others within policy and funding models.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.045 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| 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".