Food Insecurity among Elderly in The GTA
Bibliographic record
Abstract
The research focuses on individuals aged 55+, who attend food banks. A purposive sample size of 5 was selected using in-person interviews with open-ended questions. The study aims to better understand how the elderly manage food poverty in the context of global and Canadian recessions, as well as to assess their opinions of the Canadian government's effectiveness in reducing food insecurity among the elderly during the current inflation. The analysis identified seven themes: challenges in obtaining quality food, food inflation consequences, recommendations, food banks' recommendations, perceptions, government response, and future concerns. According to the study, following the pandemic, the low-income elderly are experiencing food inflation, particularly for healthy meals. People reacted by eating less healthful food and turning to food banks. Participants suggested increased government intervention, better workplaces, and better food delivery alternatives. This study focuses on a qualitative exploration of food insecurity experiences among the elderly, unlike previous quantitative studies that lacked consideration for their perspectives. The government is encouraged to take a more focused approach by incorporating the impacted population's experiences into the policy-making process. This includes building direct involvement methods, such as advisory committees to guarantee a detailed awareness of their individual difficulties and requirements.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".