Novel Conversations: Connecting With Disability in Three Examples of Popular Fiction
Bibliographic record
Abstract
Examining how readers of popular fiction respond to characters with disabilities and characters immersed in the lives of characters with disabilities, this paper serves to contribute to understandings of the meanings that readers ascribe to disability in popular culture using the public sphere of online discussion. Specifically, I study online reader discussion of three characters, namely: Trudi in Ursula Hegi’s (1996) Stones from the River, Icy in Gwyn Hyman Rubio’s (1998) Icy Sparks and Jewel in Brett Lott’s (1991) Jewel. I present findings from my analysis of reader discussion using readers’ descriptions of their identified connections with characters with disabilities. While these connections challenge the othering frequently cited in presentations of disability through readers’ recognition and appreciation of the well-rounded characters beyond traditional disability tropes, the unmet potential of reader discussion to challenge the status quo is also demonstrated through readers’ failure to expand these connections beyond the pages of the novels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".