Bibliographic record
Abstract
Gray Smith, Monique. You Hold Me Up. Illustrated by Danielle Daniel. Orca Book Publishers, 2017. Monique Gray Smith is not a prolific author, but her works have impact. She writes from her knowledge of the impact of the Indian Residential Schools on Canadian Indigenous people. Gray Smith is a mixed-heritage woman (Cree, Lakota and Scottish) who wrote this book “to remind us of our common humanity and the importance of holding each other up with respect and dignity.” “With this book,” she says, “we are embarking on a journey of reconciliation and healing.” Gray Smith uses simple terms and sentences, appropriate to a Kindergarten to Grade 3 audience, to describe the things that individuals can do in their relationships to move forward in reconciliation. Danielle Daniel’s brightly coloured, stylized illustrations reflect these concepts. The concepts include being kind to each other, sharing, learning, playing, laughing and singing together, and comforting, respecting and listening to each other. The Truth and Reconciliation Commission calls all Canadians to move forward together in reconciliation, a task that can appear to be daunting and overwhelming. Gray Smith provides a simple blueprint for small steps forward, the most basic being that we can “hold each other up.” This book is highly recommended for elementary school libraries and public libraries. Highly recommended: 4 out of 4 starsReviewer: Sandy Campbell Sandy is a Health Sciences Librarian at the University of Alberta, who has written hundreds of book reviews across many disciplines. Sandy thinks that sharing books with children is one of the greatest gifts anyone can give.
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 | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.266 | 0.147 |
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".