Bibliographic record
Abstract
This article presents results from an exploratory study of what college students from northern Ontario think about and do to manage their mental health. Data gathered in semistructured interviews were analyzed using the constant comparative method. The purpose of the study is to advance our understanding of the ontogeny, substantive nature and deployment of mental health literacy (MHL). MHL has hitherto been defined as “knowledge and beliefs about mental disorders that aid their recognition, management or prevention.”. This definition effectively translates to knowledge of the contents of the Diagnostic and Statistical Manual of Mental Disorders, currently in its fifth edition. Results of the study suggest that the current definition of MHL is overly narrow, that individuals use knowledge of various types from various sources to manage their mental health, and that the literacies that inform mental health management practices are developed through iterative engagement in autologous knowledge-translation, at the core of which are cultured resonance, meaning-making, metacognitive evaluation, and heuristic experimentation. MHL is redefined as the self-generated and acquired knowledge with which people negotiate their mental health. Broadening the definition of MHL has potential to enhance the capacity of individuals and communities to manage mental health effectively.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".