Mirrors and Windows: Teaching and Research Reflections on Canadian Aboriginal Children’s Literature
Bibliographic record
Abstract
In this reflective paper, an expanded version of my LLRC pre-conference paper, I draw on thirty or so years of teaching and research experience, augmented by the occasional foray into my childhood, to consider issues of resonance and representation in children’s literature. In doing so, I draw on Patsy Aldana’s speech, Books that are Windows. Books that are Mirrors. How Can we Make Sure that Children see Themselves in Their Books? Aldana, then President of the Canadian Coalition for School Libraries, delivered her speech to the IBBY (International Board on Books for Young People) Congress in Malaysia, 2008.[i]As a teacher and now as a teacher educator, I am reminded by Aldana’s speech to pay close attention to the children and youth who cannot take for granted, as I was able to, “hear(ing) one’s own words, see(ing) one’s own face…in a book” (Aldana, 2008).[i] In her speech, Aldana uses this metaphor as presented by Elisa Bonilla, former director of educational materials at the Mexican Ministry of Education (SEP) of Mexico, in her address to the IBBY congress in Macau, 2006.
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.087 | 0.045 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".