Early observations on the health of Syrian refugees in Canada
Bibliographic record
Abstract
Between November 4, 2015 and February 29, 2016, a total of 26,166 refugees came to Canada. Of those, only two (0.01%) were found to have signs of a notifiable disease in the Immigration Medical Examination and these individuals were referred to public health for follow-up. Most refugees - 24,640 (94.17%) - arrived by government-coordinated charter flights and underwent enhanced screening. Upon arrival in Canada, 274 refugees (1.11%) were assessed by Quarantine Officers for signs of a potential communicable disease (such as fever) and 10 (0.04%) were referred to hospital. Paramedics onsite at the airport assessed 1,212 refugees (4.92%). Fifty-four (0.22%) were transferred to hospital and many of these were known to require urgent medical care. Provincial and local public health authorities and community networks have been instrumental in providing immediate and longer-term health care to arriving refugees. The two most immediate care needs were catch-up immunizations and dental care. Arriving in Canada at the height of the influenza season, a number of refugees experienced time-limited upper respiratory infections. When referring refugees to Canadian authorities, the United Nations High Commissioner for Refugees (UNHCR) advised that the Syrian refugee population may be expected to have high medical needs. These were not necessarily identified beforehand and may include diabetes, developmental disabilities, conflict-related injuries or mental health issues. These health care needs of Syrians will be identified and addressed as they integrate into the local health care systems. The arrival of Syrian refugees in Canada has not resulted in any urgent public health concerns or need for public health intervention. Canada's experience to date indicates that the arrival of Syrian refugees in this country can be managed in a way that will integrate them into the health care system without increased risk to public health.
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) | 0.000 | 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".