Education Governance for the Twenty-First Century: Overcoming the Structural Barriers to School Reform
Bibliographic record
Abstract
Education Governance in America: Who Leads When Everyone Is in Charge?, Patrick McGuinn and Paul Manna The Failures of U.S. Education Governance Today, Chester E. Finn Jr. and Michael J. Petrilli How Current Education Governance Distorts Financial Decisionmaking, Marguerite Roza Governance Challenges to Innovators within the System, Michelle R. Davis Governance Challenges to Innovators outside the System, Steven F. Wilson Rethinking District Governance, Frederick M. Hess and Olivia M. Meeks Interstate Governance of Standards and Testing, Kathryn A. McDermott Education Governance in Performance-Based Federalism, Kenneth K. Wong The Rise of Education Executives in the White House, State House, and Mayor's Office, Jeffrey R. Henig English Perspectives on Education Governance and Delivery, Michael Barber Education Governance in Canada and the United States, Sandra Vergari Education Governance in Comparative Perspective, Michael Mintrom and Richard Walley Governance Lessons from the Health Care and Environment Sectors, Barry G. Rabe Toward a Coherent and Fair Funding System, Cynthia G. Brown Picturing a Different Governance Structure for Public Education, Paul T. Hill From Theory to Results in Governance Reform, Kenneth J. Meier The Tall Task of Education Governance Reform, Paul Manna and Patrick McGuinn
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".