The Cosmopolitans: International Students’ Identity Negotiations, Past and Present, at an Ontario University
Bibliographic record
Abstract
This research highlights the superdiversity (Blommaert, 2013; Vertovec, 2007) of undergraduate students in a university located within a large urban area in Ontario. Almost one-quarter of the total student body comprises international students, primarily from Asia. This superdiversity has created the cosmopolitans, a by-product of globally mobile students who are in pursuit of an Inner Circle English (Kachru, 1985) education. To theoretically frame the second-language socialization experiences of mobile students in English-speaking contexts, scholars have positioned cosmopolitanism at the junction of identity, language, culture, capital, and ideology (Darvin & Norton, 2016). Cosmopolitanism is a philosophy and a disposition that emphasizes openness and recognizes diversity while respectfully engaging in critical dialogue about difference (Appiah, 2006; Delanty, 2009). This study seeks to examine the role of cosmopolitanism in international students’ identity negotiations, past and present, as reflected in their dispositions and experiences while studying at a university in Ontario as well as in their recollections of their high school experiences. Elements of ethnographic and phenomenological approaches are blended with a case study method, and data have been collected and analyzed using qualitative, interpretivist methodologies. Data were collected through semi-structured interviews with 12 university students (focal participants) and two of their peers (non-focal participants), during which a Venn Diagram was used as a heuristic to discuss hybrid identity negotiations (Bhabha, 1994). Some students also completed journals. In addition, interviews were conducted with seven educational professionals to gain multiple perspectives. The research findings highlight the ways in which early study abroad experiences shape students’ identities and future choices. This study also expands the use of a tool that can be used to collect data about participants’ identities, specifically by using the Venn diagram. This dissertation provides educators with a deeper understanding of international students’ experiences. It has the potential to promote third space (Bhabha, 1994) for international students to negotiate their identities in the classroom and beyond, including those students who participate in early study abroad as adolescents.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".