BREAKING STEREOTYPES WITH CHILDREN'S FICTION: SEEKING PROTAGONISTS WITH SPECIAL NEEDS
Bibliographic record
Abstract
North American children’s authors have not been inclusive of characters with special needs when it comes to assigning the role of protagonist. While books with depictions of characters with identified exceptionalities have appeared on bookstore shelves and awards’ lists, these characters have generally been relegated to subsidiary positions, assisting other main characters in their growth and development without demonstrating parallel learning. Children require book collections which explore a broad array of characters, encouraging them to discover real life heroes within and among themselves. Scanning the list of American Newbery and Canadian Governor General’s Award winners for English text over the last twenty years, it’s interesting to note that while a number of titles for children contain characters with identifiable special needs, in all but two cases these characters are relegated to subsidiary positions. Their main purpose thus appears to be supporting the protagonist’s learning and growth, without an exploration of their own potential to develop throughout the course of the story. If these characters are created sensitively, they do not propagate stereotypes based on narrow thinking related to their particular issues or disabilities; as subsidiary characters, however, they also do not serve to correct stereotypes related to perceptions of people with exceptional needs as incapable of leadership or heroism. It is no simple oversight that books centering on characters with special needs have missed the awards lists. In fact, there is a dearth of children’s titles which illuminate characters with disabilities, in anything beyond secondary positions. Thus, while individual characters may not support stereotypes, the larger body of work for children, due to the absence of main characters with special needs, serves to continue the marginalization of people with disabilities. In books, as in society, people with challenges have been passed over for the role of hero in favour of someone whom popular culture perceives as more able to get the job done. Common stereotypes include the idea that people with exceptionalities are generally not capable, persistent, or independent, have communication difficulties, lack a sense of humour, and that a single disability is somehow all encompassing. In public, this is evidenced by someone speaking louder to a new acquaintance in a wheelchair, assuming that somehow because they are on wheels their hearing is also affected. It is apparent in the manner in which communication attempts are initially attempted through a companion, rather than directly to a person with visible differences. It has been apparent in the workplace, where people with disabilities have not historically had fair opportunities to demonstrate their worth.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".