Bibliographic record
Abstract
Minnesota and the charter public school idea / Joe Nathan -- Charter schools in California : a bruising campaign for public school choice / Priscilla Wohlstetter, Noelle C. Griffin, and Derrick Chau -- Letting a thousand flowers (and weeds) bloom : the charter story in Arizona / Frederick M. Hess and Robert Maranto -- Michigan's charter school movement : the politics of policy design / Michael Mintrom -- Colorado charter schools : becoming an enduring feature of the reform landscape / Eric Hirsch -- Massachusetts charter school initiative : a model for public school accountability? / Paul Herdman -- Wisconsin : chartering authority as educational reform / Julie F. Mead -- Parameters for choice : charter schools in Alberta / Lynn Bosetti and Robert O'Reilly -- Texas : charter schools and the struggle for equity / Lance D. Fusarelli -- Charter schools in Florida : a work in progress / Tracey Bailey, Carolyn Lavely, and Cathy Wooley-Brown -- Charter schools in North Carolina : confronting the challenges of rapid growth / Michelle Godard McNiff and Bryan C. Hassel -- New York : over 100 charter applications in year one / Sandra Vergari.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".