Spreading the Words: Promote Multiculturalism Through Innovative Community Engagement Activities.
Bibliographic record
Abstract
Background: Diversity and multiculturalism are the key tenets of Canadian culture. There is a continue need to fostering multiculturalism, thereby facilitating intercultural and intergenerational respect towards each other’s cultures. The continued inequities and racism experienced groups pointed the need of implementing innovative educational programs aimed at enhancing the knowledge of the kids and youth to raise their voices against racism and discrimination. Methods/Approach: The Centre for Research, Education, and Social Services in collaboration with the Nepalese Community Society of Calgary organized multicultural and anti-racism arts and crafts sessions (n=15) led by experts (n = 6) from diverse ethnic communities for the kids and youth (n=67). Experts were instructed to advance the knowledge of anti-racism and multiculturalism through arts and crafts along with a brief awareness component at the beginning of the session and parents were encouraged to partake. Anti-racism and multiculturalism quiz competition (n = 75) and a Canada-wide essay competition for kids and youth (n=68) were organized with the questions prepared by the experts from ethnic communities. Results/Observation: These innovative activities got a high traction of the participants and parents showed equal interest. The participants and parents got motivated to get their work showcased in one of its kind historical events, the Nepali Mela and Multicultural Showcasing Event, visited by over 10,000 visitors across Canada. The sessions led by experts from diverse ethnic communities created positive attitudes about differences and boost kids’ self-confidence in their own identities. Almost 90% of the parents highly agreed that the arts and crafts, quizzes, and essay activities helped their children engage in skill development activities that reduced screen time, enhanced social network and guardians sharing diverse cultures, and increased awareness about anti-racism and multiculturalism. The experts also affirmed that these unique activities not only increased knowledge horizons of the kids and youth engaged but the experts experienced the diverse perspective of the participants. Conclusion: The initiative increased social and emotional outcomes including social skills, self-esteem, and attitudes toward others. The issue of poor participation could be addressed by implementing the innovative activities that increase participation of the stakeholders vis-à-vis achieve project outcomes.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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".