Bibliographic record
Abstract
Le, Minh. Drawn Together. Illustrated by Dan Santat, Disney Hyperion, 2018. Drawn Together is a work of art created by Minh Le, author of award winning, Let Me Finish!, and illustrated by Caldecott Medalist, Dan Santat. This beautiful story depicts the cultural and linguistic divide between a young boy and his grandfather. The book invites the reader to walk alongside these two characters as they struggle with their differences only to stumble upon their similarities. Bringing together two generations of artists, the story revels in the characters’ imaginations as they create a vivid world of artistic adventures and compassion. Inhibited by the linguistic barriers that once isolated the characters, Minh Le’s limited, yet well crafted, text serves to support Dan Santat’s captivating illustrations that “draw” the grandfather and young boy closer. Detailed facial expressions and rich illustrations heighten the reading experience and weave together a story that both literally and metaphorically bridges the space between a grandfather and his grandson. Whether you are curling up with young ones at home or searching for a beautiful book for your classroom library, look no further. This one is guaranteed to draw you in! Highly recommended: 4 out of 4 StarsReviewer: Darcy Courtland Darcy Courtland loves a good picture book! After seven years in the classroom, Darcy has returned to the University of Alberta to pursue a PhD in Elementary Education. Always up for a new adventure, Darcy is excited to be furthering her education in language and literacy and Indigenous education.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.552 | 0.409 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".