Policy as praxis: Senior educators’ enactment of assessment policy reform
Bibliographic record
Abstract
This article reveals the multifaceted ways in which policy enactment was expressed as praxis in the context of assessment reform in Ontario, Canada. The research explores the way in which the Growing Success assessment policy was interpreted variously by different educators occupying senior roles within the district office in a single school district in northern Ontario. Drawing on neo-Aristotelian theorising, the research reveals how ‘policy in practice’ was expressed as a form of praxis, where such praxis is understood as morally committed and informed action oriented towards excellence in a field (in this case, education). While recognising the complexity of policy enactment, and how policy enactment can result in unforeseen and sometimes problematic outcomes, the research also reveals how policy enactment can have productive outcomes in relation to what are construed as the ‘internal goods’ of education. In the research presented, these productive outcomes included the capacity to facilitate teachers’ learning within and across elementary and secondary school sites; a critical, constructive focus on standardised measures of student learning in relation to academic outcomes; and the enhancement of student learning opportunities via cultural inclusion, particularly in relation to First Nations, Métis and Inuit students. In this way, the research validates a conception of policy as praxis and foregrounds how policy enactment can be understood in ways that promote the intrinsic integrity of educational practice, and the need to draw on these ‘internal goods’ in such enactment.
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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 | 0.067 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.053 |
| Scholarly communication | 0.021 | 0.008 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".