The benefits of a historical–dialectical ontology to critical mental health promotion research
Bibliographic record
Abstract
In this article, we explore challenges and opportunities in research oriented to understanding the relations among elements of socio-economic life and mental health (MH) and the development and evaluation of mental health promotion (HP) initiatives. We review the population health intervention research (PHIR) literature and respond to recommendations regarding social determinants of health and health inequities-focused research. We discuss three inter-related issue areas: first, the continued dominance of linear and individually oriented theories within predominantly quantitative research approaches and the underdevelopment of ontological and theoretical perspectives that capture complexity; second, the inconsistent use of measures of socio-economic status and health with a lack of attention to taken for granted assumptions; and third, the continued focus on measuring MH challenges to the neglect of exploring the meaning of MH in a positive sense. We extend recommendations within the PHIR literature by sharing our application of a historical-dialectical ontological perspective within a process of social praxis with diverse Canadian young people with varying degrees of access to socio-economic resources. Young people were engaged to explore the relations among socio-economic processes, young people's MH and implications for mental HP. We argue that this ontological perspective can support the development of structurally oriented critical qualitative research approaches in PHIR.
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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 | 0.048 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.007 | 0.098 |
| Scholarly communication | 0.017 | 0.029 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".