French experiences with the online courses on suicidal behaviour, their main features, requests of participants and the opportunities to foster suicide prevention
Bibliographic record
Abstract
There is a high demand for specific training on the understanding and management of suicidal behaviors. We will present a summary of a massive open online course that was launched in France in 2018 for the first time. The structure of the program was simple: 5 modules presented on a weekly basis, each module contained several short videos with direct training, interviews or discussion. The MOOC offered as well other ressources such as access to a forum during the course, an updated bibliography and vocabulary for each module and an evaluation at the end of the modules. In the first year, the number of registered candidates for the course was very high (>10000) and more than a quarter completed the course (>2500), with participants from 82 countries. The quality of exchanges with the students was very high. The results of this ongoing experience provides interesting insights on how to improve access and motivation to specific training in the field of suicidal behavior for participants from very different backgrounds. Disclosure No significant relationships.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".