Problematizing Access to Higher Education for Refugee and Globally Displaced Students: What’s the Problem Represented to Be in Canadian University Responses to Syrian, Afghan and Ukrainian Crises?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The UNHCR’s 15by30 campaign to increase refugee student enrolment in higher education to 15% by 2030 is a lofty goal. Canadian higher education institutions have a role to play in contributing to this policy goal, along with advocacy efforts from refugee student groups, community-based organizations, government, and international organizations. The aim of this study is to look critically at how the issue of access to higher education for refugee and globally displaced people is represented through Ontario’s universities’ responses to federal government initiatives to crises in Syria, Afghanistan and Ukraine. In this study, we use Bacchi’s (2009) “What’s the problem represented to be?” approach to policy analysis and, drawing on Dillabough’s (2022) critique of modernity in higher education, we argue that university responses related to refugee and globally displaced student access to higher education offer the possibility to reflect on the paradoxical tensions of the problem space in Canadian higher education. In our findings, we discuss how the problem of refugee and displacement crisis was represented differently in response to differences in geopolitical conditions and government policies, as we demonstrate how representations of material problems and categories of “citizenship” and “geographical location” in the universities’ responses contributed to creating boundaries of inclusion and exclusion for access. Finally, we show how the creation of educational programs for “globally displaced people” during the period related to the Ukrainian crisis perpetuates the logic of colonialism in the universities’ responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it