Bibliographic record
Abstract
Dear Readers,I am so grateful for the hard work and commitment of our Deakin reviewers, and I think you will share my enthusiasm for the books that they have written about for our winter issue. For example, Leslie Aitken’s review of Lila and the Crow is a wonderfully thoughtful appraisal of an important picture book deserving of a good deal of attention. Aitken writes that “Lila and the Crow belongs in every elementary school library” and I wholeheartedly agree with her assessment because this story has excellent potential to encourage positive dialogue about the physical diversity of humankind.Another highly recommended picture book is Anna Pingo’s Aluniq: and Her Friend, Buster, reviewed by Sandy Campbell. As Aluniq’s story of living with her grandparents at the Qunngilaat Reindeer Station in Canada’s Northwest Territories unfolds, readers learn that many families in remote parts of Canada experience separation when people need to leave home to receive medical treatment. The emotions that this poignant story conveys are generally ones that resonate with most readers because they remind us of one of the most significant primal fears of childhood—separation from one’s parents or guardians. For young readers coming to terms with separation, this is a charmingly illustrated and sparingly written picture book. I therefore commend it to your serious attention.Also in this issue, Lorisia MacLeod’s review of How Nivi Got Her Names calls our attention to Inuit naming customs and provides useful content for educators who want to discuss Inuit culture with young readers in the classroom.Plus, we have adventure stories, historical stories, and engaging stories of childhood and family life. Enjoy!Robert DesmaraisManaging Editor
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.441 | 0.361 |
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".