The politics of exclusion: an examination of graduate student funding experience in Ontario
Bibliographic record
Abstract
This dissertation examines the funding experiences of graduate students from diverse backgrounds. Data are collected through in-depth interviews with students pursuing Masters and Doctoral studies at three universities in Ontario. The students' experiences are discussed in the context of funding through an examination of various sites and sources, such as scholarships, assistantships, loans and paid employment outside the university. The sample reflected both funded and non-funded students in order to understand how they negotiate graduate studies and the implications for completion and career choice. Although the funding of post-secondary students has been debated at great length, much of this discussion has been focused at the undergraduate level. Graduate education and graduate students have been largely absent from these debates. Furthermore, critical discussion on social differences in Canadian graduate funding remains unaddressed. Employing qualitative methodology, this study analyzes students' experiences at various stages of their graduate studies. The findings indicate that funding is instrumental to students' progress in graduate education. Generally, students secured awards or scholarships consistently were well adjusted within their departments. These students were also more likely to complete within a reasonable time frame, but having scholarships did not necessarily mean that students complete within the required 4-year time frame specified by universities. The study also indicates that the funding provided was wholly inadequate and was a source of stress for most students. Non-funded students, especially racial minorities, working class, females, and single-parents were not only more likely to be under-funded, but they were also more likely to feel marginalized in their department. The findings suggest that graduate funding has multi-dimensional roles with important effects on the student body. Ultimately, these findings relate to issues of equity and access in the allocation of funding resources in graduate studies.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.024 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".