Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Click to increase image sizeClick to decrease image size Opinions expressed in this column do not represent views or official positions of the National Association for Multicultural Education (NAME). Similarly, reviewed resources carry no “official endorsement” by NAME. The authors are solely responsible for selecting and reviewing the resources featured in the column and strongly encourage readers to examine resources prior to purchasing. Materials submitted for review in this column should be submitted directly to any one of the reviewers at the following addresses: Ming Fang He, Dept. of Curriculum, Foundations and Reading, Georgia Southern University, P.O. Box 8144, Statesboro, GA 30460; Jeff Sapp, Division of Teacher Education, California State University at Dominguez Hills, 1000 E. Victoria Street, Carson, CA 90747; Edwidge Bryant, College of Education, School of Teaching and Learning, University of Florida, 2202 Norman Hall, P.O. Box 117048, Gainesville, FL 32611; Maria José Botelho, Dept. of Curriculum, Teaching and Learning, OISE/University of Toronto, 252 Bloor Street West, Toronto, Ontario, Canada M5S 1V6; Betty Christine Eng, Department of Applied Social Studies, City University of Hong Kong Y7429, Academic Building 83, Tat Chee Avenue, Kowloon, Hong Kong SAR; Jill Aguilar, Division of Teacher Education, California State University at Dominguez Hills, 1000 E. Victoria Street, Carson, CA 90747.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 | 0.001 |
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 it