The Rise, Fall, and Rebirth of Bilingual Education in California and the Ongoing American Dilemma
Bibliographic record
Abstract
This chapter analyzes major shifts in US educational policies toward bilingual education in California, where voters are often called on to decide policy by voting on propositions. It focuses on: how language policies have functioned as an instrument of social control; the lingering impact of the Americanization century and English-only ideologies on contemporary educational policies; the contemporary English-only movement and its impact on language minority education; and how a series of discriminatory propositions in California set the stage for language restriction in 1998. The chapter next looks at factors affecting the resurgence of bilingual education as "dual-language" education amidst discourses of globalization since 2016. The chapter concludes by noting new threats to immigrants posed by the criminalization of immigrant status and efforts to deny education as a human right. Implicit in this discussion are questions related to the relationship between language policy and racism and the salience of language policies in racial politics.
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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 | 0.000 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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".