Bibliographic record
Abstract
This study develops a conceptual understanding of the process by which provincial tuition policies undergo major change in Canada. The first research question is whether, and to what extent, two alternative theories of policy change advocacy coalition (ACF) and multiple streams of problems, policies, and politics (MSM) can explain policy change. The second research question examines how these policy processes compare to each other. This research builds upon an emerging international field of enquiry, policy and politics of higher education, and contributes important empirical, descriptive and conceptual findings to the Canadian literature on post-secondary policy. The methodology was a comparative case study of three episodes of significant policy change, selected using purposive sampling (British Columbia, Ontario, and Manitoba) and employing an analytical framework based on Ness (2008). Data were collected through systematic investigation using two key research tools: content analysis of relevant documentary materials and 59 interviews of policy actors. The research found that each of the theories provides important and relevant conceptual understanding of policy change. There are five factors associated with policy change: changing financial conditions, changing concerns about accessibility, a changing government mandate with a strong premier, changing public mood, and changing political and policy alliances. The practice of politics is central to tuition policy formation; these politics include political differentiation, brokerage politics, and retail politics. Individual universities, their presidents, and their membership organizations play an influential role in policy formation. Senior leaders within cabinet function as policy entrepreneurs, most frequently the premier. Student organizations are successful in agenda-setting. Successful influence strategies can be characterized as insider tactics, and successful agenda-setting activities include softening up. The conditions for student lobby success appear to be increased in cases where brokerage politics is occurring in an electoral contest. Research itself is not a key factor in policy change. Tuition policy choices are made with consideration of the available research; a more direct influence on policy change is political and policy learning. Regardless of policy choices and contexts, governments describe their overall policy goal as the provision of quality and accessible post-secondary education. A new conceptual model for tuition policy change is proposed.
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.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".