Exploring Intercultural Understandings of Mental Health for School Contexts
Bibliographic record
Abstract
What does mental health mean? As an educator, I have noticed that mental health is a concept viewed by many students and colleagues as “loaded” with stigma and often referenced as a shameful form of illness. It is estimated that one in five high school students will suffer from a mental illness, with the majority not accessing mental health services due to the stigma associated with the illness (Bowers et al., 2013). Wondering how particular understandings of mental health might influence pedagogical approaches, I conducted a preliminary literature review across caregiver professions, including nursing, social work, psychology, medicine and education. Findings indicated that medicalized mental health definitions framed by Western philosophy were prevalent. Conceptions of mental health that represent different cultural perspectives, pluralistic understandings (diverse epistemologies), or other ways of being (ontologies) are isolated and excluded. This roundtable session will be guided by a hermeneutic approach that aims to broaden understandings by asking participants to consider the concept of mental health within cultural traditions, histories, stories, languages, experiences, subjectivities and relations. To further discussion, contemporary conceptualizations are presented through literature, images and symbols.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.022 | 0.037 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".