Canadian Books in Canadian Schools: The Need for Teacher/Teacher-Librarian Collaboration in Reading, Knowing and Doing
Bibliographic record
Abstract
This Canadian research which explored elementary teachers’ use of, and beliefs about, Canadian children’s books in the classroom, has implications for teacherlibrarians and other educators in many countries faced with the impact of the homogenization and “Disney-fication” of children’s books and other media. The research builds on previous studies which identified some of the supports that facilitate elementary teachers’ use of children’s books in their teaching (e.g., access to teacher-librarians, funding for materials, and opportunities for professional development). The case study school district was committed to supporting the work of teachers through the school library and had these supports in place. The study participants had clear ideas about what it meant to them to be Canadian and about the values that were important to them as Canadians. They believed it was important to incorporate Canadian books into classroom activities. However, they often felt a need to justify their use of Canadian books, whereas they unquestioningly used American books in their teaching across the curriculum. Overall, they were more knowledgeable about Canadian books and Canadian authors and illustrators than teachers in earlier studies. The teachers relied on the recommendations of the teacher-librarians about books, but they rarely collaborated with teacher-librarians in selecting and using Canadian books with their students. The research report concludes with questions about lost potential in terms of the power of books to enhance children’s sense of national identity and their sense of social cohesion.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.054 | 0.011 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".