Bibliographic record
Abstract
Dwarfs, midgets, even freaks, are among the terms that have been used to label little people. Feminist theorists have argued that discursive identities of women prevent any meaningful essentialised analysis of their experiences. Similarly, disability researchers have argued against generalising the experiences of disabled individuals. This paper explores the intersection of gender and dwarfism through the narratives of four women who are little people. Findings suggest that the ways women, who are little people, negotiate public spaces are affected by discourses of gender, disability and common conceptions of what is physically normal. Furthermore, these discourses have material implications in the everyday lives of these women. A brief historical overview of dwarfism is followed by narratives that describe experiences in public spaces, perceptions of height related to age and capability, gendered spaces and sexual stereotypes, uncomfortable spaces, violations of personal space and transportation. This paper provides a partial perspective on how discourses of dwarfism are manifest in social spaces and the built environment. Despite these significant commonalities that little people shared with other disabled people, there are socio‐spatial experiences that appear to be unique to people with dwarfism.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.031 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".