Challenging fundraising, challenging inequity: contextual constraints on advocacy groups’ policy influence
Bibliographic record
Abstract
School fundraising is known to reproduce inequities in schools, yet it remains common practice in Ontario, Canada; findings from a critical policy analysis of an advocacy group’s efforts to change fundraising policy help explain why this is the case. Adopting a discursive understanding of policy, the study used rhetorical analysis to identify how the group has engaged in a decades-long struggle over the meaning of fundraising policy. The findings of the rhetorical analysis were examined in light of an historical narrative of Ontario’s social context to understand how the policy’s contexts have constrained the group’s influence. The study’s findings demonstrate that challenging school fundraising by defining the policy as a problem of equity is not strong enough to overcome neoliberalism’s pressure on parents to provide their children with educational advantages, a trend toward privatization in public education, neoconservative interests in reduced government spending, Canadians’ belief in meritocracy, and historical fundraising practices and dominant meanings. Further, the continuance of school fundraising even after Ontario’s government introduced policy that explicitly addressed the group’s concerns about equity and aimed to limit the practice challenges traditional notional of group influence and success in policy processes.
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 | 0.029 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.040 | 0.066 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".