Canadian Nutrition Society 2022 Scientific Abstracts: Canadian Nutrition Society Annual Conference
Bibliographic record
Abstract
The unique nature of Canada's 2015 initiative to resettle over 25,000 Syrian refugees within a few months raised concerns about their food security.This study aims to determine food security (FS) status of Syrian refugees in Ontario, Québec, and Saskatchewan and compare their food security status across the three major Canadian refugee resettlement programs (government-assisted refugees (GAR), privately sponsored refugees (PSR), and blended visa office referred (BVOR)).In a cross-sectional design, 282 Syrian refugee households who resettled in Ontario, Québec, and Saskatchewan since November 2015 were recruited.A validated and translated 18-item Household Food Security Survey Module used by Statistics Canada was employed to determine household food security.Overall, the rates of refugee adult, child, and household food insecurity were high (68.4%,68.3%, and 77.0%, respectively) compared to that of Canadian households (12.7% in 2017-2018).Adult food insecurity was higher among adults aged 18-40 years (79.8%) compared to older adults aged 41-60 years (30.6%) and ≥ 60 years (12.4%).Refugee households in Saskatchewan and Ontario experienced a significantly higher rate of food insecurity (87.5%, P<0.001, 79.2%, P=0.001, respectively) compared to those in Québec (52.1%).The rate of food insecurity was significantly higher among GARs compared to PSRs (79.5% vs 62.2%, P=0.039).Most households consisted of couples (89.4%), and 97% of those had children.About 78% of families with children were food insecure.In middle-income group (annual income <CAN $60,00), the proportion of food insecure households was significantly high compared to food secure households (51.2% and 27.7%, respectively, P=0.001).However, the proportion of food secure (compared to food insecure) households in the lowest income category (annual income of <CAN $15,000) was significantly higher (44.6% vs 22.1%, respectively, P<0.001).Refugees living in Ontario were 7 times more likely to be food insecure compared to those living in Québec or Saskatchewan, and middle-income refugees were 7 times more likely to be food insecure compared to high income refugees.Recent Syrian refugees remain at a high risk to food insecurity, especially in Ontario, and those with middle incomes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.416 | 0.135 |
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".