The New Common Sense of Education: Advocacy Research versus Academic Authority
Bibliographic record
Abstract
Current education policy is increasingly controlled by partisan politicians and the corporate interests that speak through them. Attacking American education and blaming economic troubles on failing schools and low standardized test scores coalesces the rhetoric of the right and draws attention away from fundamental social and economic problems. Add to this political opportunity the economic fact that attacking K–12 education leaves this market of $732 billion vulnerable to development by corporate America. Though such attacks have been with us since A Nation at Risk, an increasingly broad array of cultural and institutional forces are at work creating a new “common sense” of education that maligns or manipulates the corpus of educational research and attacks promising practices and reforms. In addition, a new type of education scholarship has emerged that is delivered in alternative ways, funded through unorthodox sources, motivated by nonacademic purposes, and supported through direct access to media and political organizations, including the federal government. This article examines the details of the new commonsense policy and rhetoric and considers what is being lost and what educators need to do to restore to public education its position of civic and moral leadership in our society.
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 | 0.077 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.018 | 0.201 |
| Scholarly communication | 0.035 | 0.059 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.020 | 0.021 |
| Insufficient payload (model declined to judge) | 0.008 | 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".