Community Centered Approaches to Inclusive Public Safety Design.
Bibliographic record
Abstract
Within 15 years, Statistics Canada (2017) predicts that more than 30% of individuals living in Canada will be part of a visible minority. The education system plays an important role in the overall experiences of this demographic, and particularly their children, often identifying the school as their initial point of personal contact with their host country. Using an arts-based engagement ethnography, a methodology designed to engage participants more meaningfully in order to capture their cultural practices and social lives in the context of their complex experiences the study explores newcomer familial experiences during the COVID-19 epidemic as they set up their lives in Canada, specifically within the context of school. Six families participated in the study. They had immigrated from Ethiopia, Pakistan, Bangladesh, the Philippines, Yemen, and Syria. The principal objective of this study was to provide context to ignite a dialogue within the educational community by repositioning newcomers’ narratives. This involved having them focus on recounting their experiences through a strength-based lens. Results indicate families were motivated to share their experiences, and established positive connections to the school, which provided them with a sense of belonging and purpose, while also nurturing their well-being and mental health. This indicated a promising point of entry for newcomer youth and their families. There was a sense of identity, purpose, religious beliefs, and solid relationships within the community. Where the responses were negative, they ranged from misunderstandings of school/cultural expectations to issues of identity, and challenges fitting in with the new community and culture. Systemic implications of this research include the criticality in addressing the academic and psychosocial needs of newcomers (e.g., improving teacher training/preparation programs). This can be accomplished by increasing awareness of newcomer families’ lived experiences, creating programming that is holistic, and providing additional supports to help newcomers overcome anxiety and isolation.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".