Feeling excluded: international students experience equity, diversity and inclusion
Bibliographic record
Abstract
Many institutions of higher education have committed to the principles of equity, diversity, and inclusion (EDI). This collective move signifies an effort to identify and confront systemic issues of marginalisation and exclusion of minoritised groups in contexts of higher education. Nevertheless, international students are not always considered an equity-seeking group, despite the structural barriers international students face. As a result, international students’ experiences of EDI remain underexplored and are typically examined from a perspective of internationalisation. The purpose of this paper is to investigate the experiences of five international students from the broader perspective of EDI at a Canadian university through a case study design. The findings demonstrate that, in spite of the university’s long-standing commitment to aspects of EDI, international students felt excluded and othered in the community. Their experiences pointed to a lack of intercultural awareness and sensitivity on the part of the superficially multicultural community, a lack of institution-led initiatives to include the students through socialisation with peers, and the limited internationalisation of the curriculum. This paper is concluded with a call for universities to recognise international students as a marginalised group in their EDI efforts and, potentially, address structural issues that internationalisation frameworks have neglected.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.023 | 0.021 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".