Bibliographic record
Abstract
War is the most serious of all threats to health (World Health Organization, 1982) and can have severe and lasting impacts on mental health. Forced displacement and migration generate risks to mental well-being, which can result in psychiatric illness. Yet, the majority of refugees do not develop psychopathology. Rather, they demonstrate resilience in the face of tremendous adversity. The influx of Syrian refugees to Canada poses challenges to the health care system. We will present our experience to date in the Ottawa region, including a multisector collaborative effort to provide settlement and health services to newly arriving refugees from the Middle East and elsewhere. The workshop will be brought to life by engaging with clinical cases and public health scenarios that present real world clinical challenges to the provision of mental health care for refugees. Objectives (1) Understand the predicament of refugees including risks to mental health, coping strategies and mental health consequences, (2) know the evidence for the emergence of mental illness in refugees and the effectiveness of multi-level interventions, (3) become familiar with published guidelines and gain a working knowledge of assessment and management of psychiatric conditions in refugee populations and cultural idioms of distress. How will the participants receive feedback about their learning? Participants will have direct feedback through answers to questions. The authors welcome subsequent communication by email. Presenters can give attendants handouts on pertinent and concise information linked to the workshop. Disclosure of interest The authors have not supplied their declaration of competing interest.
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 | 0.001 | 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 | 0.001 | 0.000 |
| 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".