East Coast Kitchen Party: A Ceilidh-Inspired Program to Reduce Social Isolation and Food Insecurity Among LGBTQIA+ Newcomers
Bibliographic record
Abstract
East Coast Kitchen Party is a ceilidh-inspired program designed and implemented in 2022 to reduce the impacts of social isolation and food insecurity as a pathway to improving the mental wellness of lesbian, gay, bisexual, transgender, queer or questioning, intersex, and asexual (LGBTQIA+) newcomers in Halifax, Nova Scotia, Canada. Developed through a partnership between Nova Scotia Health Mental Health and Addictions Health Promotion and the YMCA Centre for Immigrant Programs, the program combined cultural cooking activities, nutrition education, and mental wellness workshops. The program emphasized peer-to-peer learning, leadership development, and culturally responsive mental wellness practices. Six sessions were held between June 2022 and February 2023, engaging 6-10 participants each. Each session invited participants to share a culturally significant recipe, fostering pride, storytelling, and connection. Discussions following the meals addressed themes such as transitioning to life in Canada and building community, with interpretation services ensuring accessibility. Evaluation through surveys and oral feedback informed iterative improvements. Challenges included food affordability, participant transience, and varying support needs based on immigration status and time in Canada. Despite these, the program successfully created inclusive spaces for LGBTQIA+ newcomers to connect, share, and heal. The initiative highlighted the importance of meeting participants where they are, recognizing the diversity within the newcomer experience, and using food as a bridge to build trust and community. The success of East Coast Kitchen Party has inspired interest in expanding the model through new partnerships, aiming to deepen connections between LGBTQIA+ newcomers and the broader community.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".