Students’ aid policies: a comparative mixed-method study of two federal cases
Bibliographic record
Abstract
In the last decades, OECD countries witnessed more than one way of designing students’ aid policies, under a predominant trend of decentralizing their governance. However, this decentralizing process carried the seeds of its own contradictions. The central paradox is that these policies remained multi-issue and multi-actor, making them likely to fall under the double-hand of different governmental levels. Federal countries constitute a laboratory to study the “decentralization experiment” in its absurdity. For this reason, the PhD project proposes a comparison between two federal cases (i.e. the United States and Canada), and in time (between 1930 and 2018), using a mixed-method. The analysis is also extended in a discussion of four embedded deviant case studies (Alaska, New York, Prince Edward Island and Quebec). Albeit usually simplified as paradigmatic cases for liberal, elitist, loan-oriented and tightfisted aid systems, the United States and Canada have proved to be more generous over student aid than what is expected from their respective welfare regime. Nevertheless, behind this engagement, I uncover an intergovernmental contention of powers and responsibilities embedded within deeply rooted federal institutions. With a focus on federal structures and dynamics, I also reveal potential political and economic incentives behind student aid. Beyond the common belief that students’ aid exists solely to help students, the thesis shows how these policies might be more grounded in institutional factors than student- related considerations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 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".