A Mixed Methods Exploration of Students' Experiences of Taking Part in a Tuition Assistance Program in Rural Alberta, Canada
Bibliographic record
Abstract
This paper reports on the experiences of rural students taking part in the Zero Fee Tuition program—a postsecondary tuition assistance program providing up to $5,000 in tuition subsidies for students residing in Drayton Valley, Alberta, Canada. Zero Fee Tuition was introduced by the Town of Drayton Valley in 2019 as a rural development initiative focused on attracting and retaining postsecondary education students. Here, we present a qualitatively-oriented mixed methods study of interview, focus group, and survey data collected with 24 Zero Fee Tuition students in 2021-2022 as part of a broader community-based participatory research project. In this paper, we explore two overarching themes: (a) facing opportunities and challenges throughout zero-fee tuition education, and (b) shifting the culture of education and training in Drayton Valley. Our results suggest that students' experiences were heavily shaped by the gendered care work they undertake in addition to, and as part of, their paid work and studies. Further, the Zero Fee Tuition program provided many students the first opportunity to attend a postsecondary education program. In this way, our findings suggest that Zero Fee Tuition is working towards its goal of expanding educational opportunities for residents of Drayton Valley. We discuss our findings within a rural oil-based town shaped by a boom-bust economy. Despite the positive contributions of the Zero Fee Tuition program, our analysis demonstrates the persistence of social structural conditions that impact the challenges faced by participants in this study.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".