What Doesn’t Work: The Challenge and Failure of the What Works Clearinghouse to Conduct Meaningful Reviews of Studies of Mathematics Curricula
Bibliographic record
Abstract
An early version of this article, discussing curricular interventions in mathematics, was written for the What Works Clearinghouse (WWC). The Institute of Education Sciences (IES), which funds WWC, instructed WWC not to publish it. An expanded version, written at WWC’s invitation for a special issue of an independent electronic journal and a book to be published by WWC, argued that methodological problems rendered some WWC mathematics reports potentially misleading and/or uninterpretable. IES instructed WWC staff not to publish their chapters—thus canceling the publication of the special issue and the book. Those actions, chronicled here, raise important issues concerning the role of federal agencies and their contracting organizations in suppressing scientific research that casts doubt on current or intended federal policy.
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 | 0.527 | 0.754 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.021 | 0.015 |
| Science and technology studies | 0.011 | 0.036 |
| Scholarly communication | 0.032 | 0.042 |
| Open science | 0.009 | 0.011 |
| Research integrity | 0.020 | 0.026 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".