A position paper on researching braille in the cognitive sciences: decentering the sighted norm
Bibliographic record
Abstract
Abstract This article positions braille as a writing system worthy of study in its own right and on its own terms. We begin with a discussion of the role of braille in the lives of those who read and write it and a call for more attention to braille in the reading sciences. We then give an overview of the history and development of braille, focusing on its formal characteristics as a writing system, in order to acquaint sighted print readers with the basics of braille and to spark further interest among reading researchers. We then explore how print-centric assumptions and sight-centric motivations have potentially negative consequences, not only for braille users but also for the types of questions researchers think to pursue. We conclude with recommendations for conducting responsible and informed research about braille. We affirm that blindness is most equitably understood as but one of the many diverse ways humans experience the world. Researching braille literacy from an equity and diversity perspective provides positive, fruitful insights into perception and cognition, contributes to the typologically oriented work on the world’s writing systems, and contributes to equity by centering the perspectives and literacy of the people who read and write braille.
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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 | 0.030 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.037 |
| Scholarly communication | 0.011 | 0.022 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".