Global Mental Health: sharing and synthesizing knowledge for sustainable development
Bibliographic record
Abstract
Global mental health (GMH) is a growing domain with an increasing capacity to positively impact the world community's efforts for sustainable development and wellbeing. Sharing and synthesizing GMH and multi-sectoral knowledge, the focus of this paper, is an important way to support these global efforts. This paper consolidates some of the most recent and relevant 'context resources' [global multi-sector (GMS) materials, emphasizing world reports on major issues] and 'core resources' (GMH materials, including newsletters, texts, conferences, training, etc.). In addition to offering a guided index of materials, it presents an orientation framework (global integration) to help make important information as accessible and useful as possible. Mental health colleagues are encouraged to stay current in GMH and global issues, to engage in the emerging agendas for sustainable development and wellbeing, and to intentionally connect and contribute across sectors. Colleagues in all sectors are encouraged to do likewise, and to take advantage of the wealth of shared and synthesized knowledge in the GMH domain, such as the materials featured in this paper.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".