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
School libraries in the United States of America have recently experienced an unprecedented number of external censorship attempts. Some censorship attempts, however, quietly occur when the school librarian engages in self-censorship, removing or refusing to purchase materials they consider to be controversial. This collection analysis study explored the extent of self-censorship in 90 Texas public high school libraries based on the exclusion of 55 controversial books in their collections, examining (1) possible relationships between a school’s characteristics and the absence of controversial books, (2) the extent to which the librarians are engaging in self-censorship, and (3) the controversial topics least likely to be included in collections. Findings suggest campus enrollment and district size were moderate to strong predictors of the number of expected books in a school library. More than half of the school libraries had the number of books one would expect based on their district size and campus enrollment. Books with transgender or LGBTQIA+ content were less likely to be found in school libraries, whereas titles featuring profanity, drinking, and drug use were most likely to appear, regardless of campus, district, and city size.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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