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
Contents: Preface. Introduction. Part I: Essential Research on Success for All. R.E. Slavin, N.A. Madden, Success for All: An Overview. R.E. Slavin, N.A. Madden, Summary of Research on Success for All and Roots & Wings. S.M. Ross, L.J. Smith, Success for All in Memphis: Raising Reading Performance in High-Poverty Schools. Part II: International Adaptations of Success for All. A. Harris, D. Hopkins, J. Wordsworth, The Implementation and Impact of Success for All in English Schools. B. Chambers, P.C. Abrami, S. Morrison, Can Success for All Succeed in Canada? Y. Center, L. Freeman, G. Robertson, A Longitudinal Evaluation of the Schoolwide Early Language and Literacy Program (SWELL). R. Hertz-Lazarowitz, Success for All: A Community Model for Advancing Arabs and Jews in Israel. M. Calderon, Success for All in Mexico. Part III: Implications for Policy and Practice. R.E. Slavin, N.A. Madden, Disseminating Success for All: Lessons for Policy and Practice.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.007 | 0.000 |
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