From Whitman to Hugo: An interview with Brian Selznick
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
‘Walt Whitman loved words’. So begins Barbara Kerley’s and Brian Selznick’s Walt Whitman: Words for America (2004), a biography of the American poet for young readers that has been recognized as a Robert F. Sibert Honor Book. Kerley and Selznick trace the poet from his beginnings as a printer’s apprentice to his volunteer work as a nurse during the American Civil War; and from the young Walt poring over the pages of Arabian Nights and Ivanhoe to his own creative output being interpreted as the voice of his nation. Like all of Selznick’s books, Walt Whitman is illustrated with precise, evocative drawings for all ages. The New York Times bestselling author and illustrator returns to the poet with his latest, Live Oak, with Moss (2019). Among Selznick’s many other popular books for children are The Invention of Hugo Cabret (2007) and Wonderstruck (2011) (covers available at https://www.thebrianselznick.com/books.htm ). These two works have now been adapted into award-winning films by Martin Scorsese (2011) and Todd Haynes (2017), respectively.
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) | 0.009 | 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