Exploring the limits of 21st century educational change discourses
Bibliographic record
Abstract
This paper discusses the discourses surrounding an ambitious high-school transformation project in a large Canadian city that sought to reimagine education for 21st century learning. It was grounded in a broad review of the latest educational research. While an initial eight schools signed on, by the end of the second year all had left the project. Drawing upon Gee's ([2005]. An introduction to discourse analysis: Theory and method. New York, NY: Routledge; [2014]. How to do discourse analysis: A toolkit. New York, NY: Routledge) tools for analyzing ‘Knowledge Building’ discourses, we explore how the project's communications produced tensions and contradictions, which reflect similar ones within the global research discourses on educational change. Key elements include strong branding, inconsistent messaging over objectives and ownership, centralized control and external sources of authority, a ‘start fresh’ ethos, and unfamiliar educational values from systems and design thinking. Ultimately, neoliberal assumptions about the means and ends of schooling embedded in the 21st century change discourses undermined the collaborative and teacher driven stated aims of the project.
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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 | 0.057 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.038 | 0.166 |
| Scholarly communication | 0.046 | 0.031 |
| Open science | 0.005 | 0.027 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".