A Duoethnographic Exploration of Race and Gender: A Dialogue Between Female International Students in Canada
Bibliographic record
Abstract
The number of international students in Canadian universities has dramatically increased since 2000. International students are believed to contribute significantly to education and research, as they bring a rich variety of perspectives, experiences, and languages. However, international students should not be categorized into one homogenous group. In particular, international female PhD students have many different reasons to immigrate and undertake a rigorous academic program. Whether to pursue high academic goals, gain personal knowledge, develop research skills, or widen employment opportunities, each student carries a different cultural background that informs their decisions prior to their arrival, their transitions, their adjustments, and subsequently their participation in the new culture. Using a duoethnographic dialogical approach and ideas about bonding beyond race and culture, this article focused on the experiences of two female international PhD students from Costa Rica and Nigeria as we answered questions regarding the intersections between race and gender within our processes behind mobility to Canada. Key words: duoethnography, international students, race, culture, gender Le nombre d'étudiants étrangers dans les universités canadiennes a augmenté de façon spectaculaire depuis 2000. On estime que les étudiants étrangers contribuent de manière significative à l'éducation et à la recherche, car ils apportent une riche variété de perspectives, d'expériences et de langues. Cependant, les étudiants étrangers ne doivent pas être classés dans un groupe homogène. En particulier, les doctorantes internationales ont de nombreuses raisons différentes d'immigrer et d'entreprendre un programme universitaire rigoureux. Qu'il s'agisse de poursuivre des objectifs universitaires élevés, d'acquérir des connaissances personnelles, de développer des compétences en matière de recherche ou d'élargir les possibilités d'emploi, chaque étudiante possède un bagage culturel différent qui influence ses décisions avant son arrivée, ses transitions, ses ajustements et, par la suite, sa participation à la nouvelle culture. En utilisant une approche dialogique duoethnographique et des idées sur la création de liens au-delà de la race et de la culture, cet article porte sur les expériences de deux doctorantes internationales du Costa Rica et du Nigéria alors que nous répondions à des questions concernant les intersections entre la race et le genre dans nos processus qui sous-tendent le déplacement vers le Canada. Mots-clés : duoethnographie, étudiants internationaux, race, culture, genre.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.058 | 0.020 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| 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".