Patterns and Themes in Canadian Picture Books Published in 2017: A Content Analysis of 132 Titles Using Dresang’s Lens of Radical Change
Bibliographic record
Abstract
This comprehensive examination of 132 picture books originally published by Canadian publishers in 2017, and written and/or illustrated by at least one creator living in Canada, offers qualitative and quantitative findings that demonstrate patterns and themes in relation to number of titles, authors, illustrators, characters, genres, audiences, and readability characteristics, while addressing particular elements of Dresang’s (1999) notion of Radical Change. Books were identified from multiple sources with results compared to a previous study (Author 3), demonstrating a marginal increase of titles since 2015 where 120 books were identified, and a continued increase from 2005 where 57 books were identified. Of particular note in the current sample were the 13 books created by Indigenous authors and/or illustrators and presenting Canadian Indigenous content and perspectives, calculated at 9.8 % of the study sample, compared to previous results where books by Indigenous authors and/or illustrators comprised 3.5 % of the sample in 2005 and 10% in 2015. These findings, and other patterns, themes and possible trends, are suggested as underpinnings for future research involving further changes in the field of Canadian children’s literature in education as well as further research into reader response regarding contemporary titles. While this paper does address aspects of diversity present in this study sample, a second article disseminates detailed findings related to representations of ethnicity.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.017 | 0.034 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".