A study of the Canadian student visa application experience of Nigerian international graduate students in Canada.
Bibliographic record
Abstract
This study explores the student visa application experiences of Nigerian international graduate students at the University of Manitoba and addresses the research question: how do Nigerian international graduate students at the University of Manitoba perceive the Canadian student visa application process based on their experiences? The purpose of this research is to increase awareness of the visa application challenges and concerns of Nigerian international graduate students applying to study in Canada—with the intention of informing future policy and research. This study uses Giddens’ (1984) structuration theory to examine the effect of the bureaucratic structure (Canada’s visa system) on individual student agency, as evident in how individuals’ goals are modified to fit within the structural requirements. Critical race theory is also used to examine how racism and its various intersections affect student visa requirements and outcomes. Semi-structured interviews were conducted with nine Nigerian international graduate students at the University of Manitoba, each of whom had applied for a Canadian student visa from Nigeria using a Nigerian passport. Three sub-themes related to the bureaucratic complexity of the visa application process emerged from the interview data: “life on hold” (the process was laborious with no definite timeline regarding how long the wait for a decision would be, which resulted in life delays, stress and emotional turmoil); “social networks and social capital” (students commented on the importance of peer groups and online sources in navigating the visa process); and “discrimination” (students discussed the influence of race and other intersecting forms of discrimination on visa outcomes). Several recommendations and future research directions are also discussed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.032 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".