The representation of disability in children's literature
Bibliographic record
Abstract
The representation of disability in children’s literature in an area that is severely under researched yet is something that is relevant to us all. Disability is an extremely fluid minority, with people moving between the able-bodied and the disabled throughout their lifetime, some on multiple occasions. It is therefore extremely important that the representation of disability in our literature, particularly in children’s literature, is one that is accurate and diverse. This thesis will be examining the way that disability is created within society based on our understanding of ‘the norm’ and the way we perceive the body. I will be discussing the binary relationship between the able-bodied and the disabled throughout this thesis and the need to break down socially constructed barriers and reclassify these two groups. I will be examining the way characters with a disability and ‘the body’ are treated within two classic children’s texts, J.M. Barrie’s Peter Pan and Victor Hugo’s The Hunchback of Notre Dame, before progressing on to a contemporary children’s text Finding Nemo. Additionally, I will be conducting a close analysis of two recent picture books, The Black Book of Colours by Menena Cottin, originally written in Spanish, and the Indigenous Australian text Two Mates by Melanie Prewett.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.015 | 0.040 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".