'Score! You Are Now More Canadian': A Case Study Approach to Understanding Citizenship and National Belonging in Sport
Bibliographic record
Abstract
This thesis explores the concept of sport as a vehicle of belonging and negotiating identity via case study of the Umoja Games, an annual faith and community-based sport tournament held in the United States and Canada. This study explores the narratives of the players and the co-founder combined with data collected through the Umoja Games social media to understand the ways in which identities, ideas of citizenship and the sense of belonging to the nation are negotiated, constructed, and understood by participants. The Umoja Games becomes a unique setting in which transnational movement, political/social climates, and multiple identities are highlighted and pushed to the foreground allowing for an in-depth analysis of the undergoing negotiation processes of identity building and belonging. This study utilizes the foundational assumptions of post-colonial theory and social constructivism lens to conceptualize, examine, and analyse identity and the notions of belonging. \nThis study reveals multiple interconnected themes that allow for a better understanding of second-generation bicultural identities and the ways in which the sense of belonging is negotiated given such identities. Utilizing Antonsichs (2010) analytical framework avoids the conflation of belonging to identity and citizenship, revealing the nuances behind the participants feelings of belonging as multi-scalar, interwoven with their own experiences, relational, cultural, economic, and legal factors. Participants understanding of their own identities proves to be complex, supporting existing research that emphasizes the negotiation process between two identities. However, this negotiation surpasses the binary of finding the balance between two cultures instead participants narratives indicate that identity negotiation exists in the Third Space (Bhabha, 1994). The socio-political, environmental, and cultural conditions that participants describe as Muslim Canadian citizens significantly impacted the ways in which participants experience sport (both mainstream and community) as well as the ways they come to understand their identities and sense of belonging to the nation.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.037 | 0.020 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 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".