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
Policies designed to improve educational outcomes in the United States (and many other countries) over the past decade have failed to raise overall achievement or close the gap between middle-class and low-income students in any significant way. Little tangible impact is evident despite the expenditure of billions of dollars ($6 billion for the Reading First program alone). Alienated adolescents, primarily from culturally and linguistically diverse backgrounds, continue to drop out of high school in large numbers. I argue that the persistent failure of educational policies designed to close the achievement gap is largely a result of implementing evidence-free policies and instructional practices. Policy-makers have chosen to ignore extensive empirical evidence suggesting the following: (a) factors associated with socioeconomic status (SES) and broader patterns of societal power relations exert a major influence on educational outcomes; (b) literacy engagement is a stronger predictor of reading performance than socioeconomic status (SES), and low-income students have significantly less access to books and print than do higher-income students; (c) students will engage academically only to the extent that classroom interactions and academic effort are identity-affirming. The framework proposed for stimulating school-based policy discussions argues that school polices need to maximize print access and literacy engagement among marginalized group students and in addition that they need to enable students to use language and literacy in ways that will affirm their identities and challenge the deficit orientation that is frequently built into programs and curriculum for low-income and bilingual learners.
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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it