Providing for the Priceless Student: Ideologies of Choice in an Emerging Educational Market
Bibliographic record
Abstract
The growing popularity of school choice is typically linked to the spread of neoliberal ideology. Identifying four components of this ideology, we examine the rationales of providers in an emerging private school market. Data come from interviews and site visits at 45 “third‐sector” private schools in Toronto, Canada. We find that only one of the four components has a strong resonance among these educators. Few private school operators sharply criticize public schools, compete via quantitative performance indicators, or are strongly business oriented. However, they voice a philosophy of matching their personal talents to the needs of “unique” children. Overall, rather than being influenced by neoliberalism, these providers are more directly driven by personalized rationales that prize tailored education in specialized niches. We draw two conclusions from these findings. First, they demonstrate how ideologies of choice are shaped by their market setting, in this case, small proprietorship, in contrast to a corporate environment. Second, they highlight how providers can be motivated by new cultures of consumerism and intensive child rearing when working in highly uncertain conditions. We recommend that theories of choice recognize the range of educational markets and the specific motives of their providers.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.034 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".