Belonging through participation: an exploration of the Caribana, Pride, and Santa Claus parades in Toronto, 1998-2004
Bibliographic record
Abstract
This exploratory, qualitative study is anchored in the critical research tradition. It examines three celebratory street parades in Toronto: the Caribana, Pride, and Santa Claus parades within a seven year time period. By considering these parades as informal sites of education, it attempts to address a set of research questions that seeks to understand the role and contribution of these parades to the socio-cultural aspects of parade participants' citizenship. The questions are framed within a problem that sees the lack of a sense of belonging as an impediment, among others, to the realization of full citizenship for 'visible minority' citizens in Canada. Triangulated in data collection methods and aided by visual data, this study finds that each of the parades commands its own ethno-cultural constituency. By providing a participatory space and various forms of utilities, these parades also enrich the socio-cultural dimensions of parade participants' citizenship, and as a result they enhance a sense of belonging for the communities associated with them. The researcher argues in favour of tangible public supports for cultural events such as parades, especially for the events that have marginal groups as their primary constituencies, as an effective means to address the problem of social exclusion. This study identifies five broad processes in the parades that contribute to parade participants' sense of belonging. It also identifies and critically examines the roles and contributions of fifteen major direct and indirect parade components which contribute to the creation of such a sense. In the tradition of critical pedagogy and cultural studies, these findings are expected to contribute to the nearly non-existent field of informal civic education involving ethno-cultural celebratory public events. The stakeholders associated with such events, educators, social justice activists, policy makers, artists, and producers of cultural festivities who wish to facilitate civic participation and social cohesion among people to enrich the socio-cultural dimensions of Canadian citizenship, may use the findings of this study as empowering knowledge in their tasks for designing, evaluating, managing, and improving the civic contributions of these events.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".