Shifting meanings: The struggle over public funding of private schools in Alberta, Canada
Bibliographic record
Abstract
The government of Alberta, Canada, has provided public funding to eligible private schools since 1967. This policy has always been contested, and in this article, we explain how we applied concepts from argumentative discourse theory and its attendant methodology, argumentative discourse analysis (ADA), to trace the debate over the policy since 1990. Argumentative discourse theory posits that policymaking involves struggles for discursive dominance wherein actors try to convince others to view the policy issue in a particular way. Drawing on 158 media articles, interviews, and secondary sources, we show that although some of the actors in the dispute have changed – and changed sides – their arguments have remained fairly consistent. However, their arguments’ meanings – and of the policy itself – have changed as the dominant discourse in the province shifted. Specifically, in response to the rise and predominance of neoliberalism in Alberta, supporters redefined the policy to fund private schools with public money as one that promoted choice and competition that would improve schooling. Opponents, on the other hand, recast the policy as part of a larger government effort to privatize public education. We demonstrate that argumentative discourse theory and ADA can be used to support the goals of critical policy analysis.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.039 | 0.023 |
| Scholarly communication | 0.019 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".