An interpretive policy analysis of Steps to English Proficiency (STEP): Examining the space for plurilingual approaches for students with emerging print literacy in English Literacy Development (ELD) classes in Ontario
Bibliographic record
Abstract
This thesis explores how the Ontario Ministry of Education’s Steps to English Proficiency (STEP) framework shapes the experiences of multilingual learners with emerging print literacy, particularly students from refugee backgrounds placed in English Literacy Development (ELD) programs. Drawing on Hilary Janks’ (2004) Access Paradox and posthumanist theory (Barad, 2007; Pennycook, 2018; Van Viegen, 2020), I examine STEP as a material and symbolic artefact—one that moves through raciolinguistic hierarchies, settler colonial systems, and everyday classroom practice. I used interpretive policy analysis (Yanow, 2000, 2007, 2010; Moore & Wiley, 2015) to consider STEP from the perspectives of educators, school boards, and academic experts. I included interviews with educators and academic experts, a content analysis of Ontario school board websites, and reflexive engagement with artefacts like a school board ethics rejection letter and an erasure poem created from STEP itself. STEP emerged as useful, problematic, contested, and worth reimagining. As a mediant, STEP holds contradictions and potential, enabling and constraining the educators who engage with it and the students whose lives and academic trajectories are shaped by its use. I argue that STEP, despite its contradictions, can offer a starting point for embedding and spreading plurilingual, justice-oriented practices into a grounded policy that already lives in Ontario classrooms in the hands of educators. However, for this reimagining to matter, the process must be transparent and include the input and lived knowledge of former students, families, and communities in meaningful ways
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.029 | 0.035 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| 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".