Understanding the acculturation experiences of immigrant athletes within the Canadian sport system
Bibliographic record
Abstract
Societies are in constant evolution and have become more culturally and ethnically diverse. One of the contributors to this diversity is the movement of people between/within countries. Although the reason for relocating to an unfamiliar country or context varies for these individuals relocating (Berry, 1997; Berry, Poortinga, Segal, & Dasen, 2002), they all face the task of navigating between their home culture and a new culture (i.e., that of the receiving community). Acculturation refers to a process of psychological and socio-cultural change and adjustment to unfamiliar cultural practices, such as in eating patterns, dress, and language, which an immigrant undergoes to align with the dominant societal group (Schinke, McGannon, Battochio, & Wells, 2013). The acculturation process of immigrants has been considered from various disciplines (e.g., psychology, sociology, and sport psychology) and various theoretical approaches (e.g., positivist, interpretivist, and social constructionist) have been used to examine this concept. Within this dissertation, acculturation was examined through a critical sociocultural and interdisciplinary position to better excavate into the stories of sport participants in multicultural societies. This project was designed to advance acculturation research area by examining the stories told by immigrant athletes about their acculturation challenges within their sport and non-sport contexts from a critical epistemological position (Chirkov, 2009a; Schinke & McGannon, 2014), the impact of such challenges, and multi-level strategies they utilized to overcome such challenges. Data was collected using the following four methods: (a) arts-based approaches focused on representation of the athletes’ daily routine, (b) conversational interviews, (c) guided journey, and (d) fieldnotes. Moving stories were the culmination of the four data sources and were used to tease out and bring to light the athletes’ stories and voices, allowing readers to vicariously learn from their acculturation journeys. The data analysis was done using an interpretive thematic analysis (ITA), followed by the development of composite moving stories. Two overarching themes were driven by my engagement with the data and methods; (a) role of family (sub-themes; family support, athlete-family settlement conflicts, times and mutual understanding) (b) role of community-sport community (sub-themes; immersion through communication and creating relationships, exchange of goals and values, skill level, openness creates ease of communication, preserving home, and culture and accepting the new). The moving stories within theme one allows for the highlighting of the complicated web of relationships (i.e., struggles between competing cultural narratives of expectations) and the role that each member of the family played in helping the athletes achieve success. The stories within the second overarching theme allow for the highlighting of vacillations (i.e., integrating within the receiving community while preserving cultural practices of home culture) as the immigrant athletes engaged in and experienced the receiving community. The findings contributed towards the acculturation scholarship in sport psychology by providing highly contextualized insights into how athletes navigated their transition between cultures as they progressed through their day. The use of moving stories as a form of representation extended this research area by offering the reader an opportunity to think along with the athletes and learn through an embodied response to the complex relocation stories encountered by elite immigrant athletes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.010 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".