Equity-oriented food supports: Learnings from the Nova Scotia COVID-19 pandemic response
Bibliographic record
Abstract
SETTING: Public health measures enacted during the COVID-19 pandemic significantly impacted Nova Scotians experiencing food insecurity. Public Health (PH), Nova Scotia Health, created a provincial Housing Isolation Program (HIP) which addressed barriers to isolation, including food access, for COVID-19 cases and contacts being followed by PH. INTERVENTION: HIP worked with partners to coordinate and respond to urgent food needs of isolating clients by providing grocery and meal delivery options. HIP also made referrals to government and community partners for income and food supports. This program was intended to minimize the spread of COVID-19 by facilitating isolation while meeting basic needs for people with no other means of support. OUTCOMES: From December 2020 to March 2022, HIP completed grocery and meal deliveries for 579 clients, 1351 referrals to a provincial Income Support Program, and 231 referrals to external food supports. HIP staff worked with clients to manage potential perceptions of stigma. Challenges reported included the urgency of food needs, lack of social supports, and availability and accessibility constraints in rural communities, as well as difficulty accessing culturally appropriate foods and special diets. IMPLICATIONS: This intervention demonstrates the importance of addressing food insecurity during emergency preparedness, planning, and response. During emergencies, planning and mobilizing food access requires an equity-oriented approach to overcome stigma. Broadly, continued reliance on charitable responses creates significant vulnerability during emergencies and addressing root causes of food insecurity through social policy will provide longer-term protection.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".