Mobilizing public alternative schools for post-neoliberal futures: Legacies of critical hope in Philadelphia and Toronto
Bibliographic record
Abstract
Starting in the late 1960s, alternative schools were established in many public school districts across North America. These programs tended to embrace humanizing ideals and sought to center self-expression, creativity, and non-hierarchical values in school governance models. While alternative schools persist today, many now embrace a range of historically situated values—often layering market-based ideals onto the language and structures of their humanizing commitments. This article explores the historical entanglements of public alternative schools, humanizing pedagogies, and market-based ideals in the Philadelphia and Toronto contexts in order to consider what structures of the past might be of use in reimagining public education for the future. In so doing, we argue that such programs, when augmented by a commitment to critical hope, offer generative possibilities for reimagining and redefining schools for the post-neoliberal future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".