Perceived barriers in accessing food among recent Latin American immigrants in Toronto
Bibliographic record
Abstract
OBJECTIVE: In Canada, recent immigrant households experience more food insecurity than the general population, but limited information is available about the personal, cultural, and social factors that contribute to this vulnerability. This study focused on recent Latin American (LA) immigrants to explore their perceived barriers in acquiring safe, nutritious, and culturally-appropriate food. DESIGN: A cross-sectional mixed-method design was applied to collect information from a convenience sample of 70 adult Spanish/Portuguese speakers who had arrived in Toronto within the last five years. Face-to-face interviews were conducted with primary household caregivers to obtain responses about barriers to acquiring food for their households; data were analyzed using a thematic analysis technique. RESULTS: Four main categories of barriers were identified: limited financial resources; language difficulty; cultural food preferences; and poor knowledge of available community-based food resources and services. Inadequate income was the main impediment in accessing adequate food, and was related to affordability of food items, accessibility of food outlets and transportation cost, and limited time for grocery shopping due to work conditions. Language barriers affected participants' ability to obtain well-paid employment and their awareness about and access to available community-based food resources. Cultural barriers were related to food preferences and limited access to culturally-appropriate foods and resources. CONCLUSION: The main barrier to food security among our sample of LA newcomers to Toronto is limited financial resources, highlighting the need for policies and strategies that could improve their financial power to purchase sufficient, nutritious, and culturally-acceptable food. Linguistic barriers and limited information among newcomers suggest the need to provide linguistically- and culturally-appropriate information related to community-based food programs and resources, as well as accessible subsidized English language programs, in the community and at workplaces. Participatory community-based food programs can augment, in a socially acceptable manner, food resources and reduce the social stigma attached to food charity. Finally, it is crucial to monitor and evaluate existing social and community-based services for their accessibility, cultural appropriateness and diversity, and effectiveness.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".