Critical policy analysis in education: Exploring and interrogating (in)equity across contexts
Bibliographic record
Abstract
This article is the introduction to a special issue of Education Policy Analysis Archives entitled, “Critical Policy Analysis in Education: Exploring and Interrogating (In)Equity Across Contexts.” The special issue presents contemporary critical policy analyses from the United States, Canada, and Australia, which collectively represent methodological, contextual, and theoretical diversity. Individually, they offer incisive critiques of policy processes and outcomes that shape the way equity, and indeed inequity, are manifest in situ. The articles represent a spectrum of approaches to understanding (in)equity in education and point out various ways that educators, scholars, policymakers, and activists can engage with systems to leverage change. In the article, the co-editors identify key themes that distinguish the special issue’s contribution and explain the importance of critical policy analysis as a relevant and necessary alternative to policy analyses that ignore issues of equity, social justice, and oppression.
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 | 0.056 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.014 | 0.060 |
| Scholarly communication | 0.032 | 0.023 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.013 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".