TOWARDS CUSTOMIZED PRIVATIZATION IN PUBLIC EDUCATION IN BRITISH COLUMBIA: THE PROVINCIAL EDUCATION PLAN AND PERSONALIZED LEARNING
Bibliographic record
Abstract
Corporate school reform is a global movement that is gaining a growing momentum. Central to this reform agenda is personalized learning , presented by its advocates as a better alternative to the traditional model of schooling. In spite of its appealing possibilities for education and society, scholars in countries such as the United States and the United Kingdom have criticized personalized learning for its reductive conceptualization of education. Focusing critically on the new Education Plan of British Columbia, which places personalized learning at its core, this paper examines the genealogy of the Education Plan and discusses its implications for public education in the province. Through construction of a network of actors and content analysis of key documents produced by the public and private sectors, the paper shows that the vision of the Education Plan is largely influenced by a broader neoliberalism-oriented social imagination reinforced by a network of political, social, and economic actors. The analysis shows that this vision for education promotes a perception of education primarily conceptualized in narrow economic terms. The discourse and practice employed to promote personalized learning contribute to turning education into a customizable consumer product, reduce the notion of “learning” to a list of skil ls and attributes, disregard the significant importance of socio-cultural contexts in teaching and learning, and minimize the crucial role of the teacher. The article concludes that the Education Plan has created a conducive environment for the emergence of customized privatization in public education in the province.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".