The reading experience through deaf eyes : a case study of signing deaf high school students
Bibliographic record
Abstract
A qualitative case study explored the reading experiences of two Deaf high school students from a sociocultural perspective that recognizes Deaf readers as part of a language and cultural minority. Consistent with a sociocultural perspective, these case studies described the participants' cultural, language and school background followed by details about their reading experiences in the context of a School for the Deaf, the Deaf culture and community as well as their home and larger community. Volunteer participants had a Deaf cultural identity and participated in social activities within the Deaf community, communicated in American Sign Language (ASL) and read at a Grade 3 reading level, or above (results from the Stanford Achievement Test, Ninth Edition). Multiple sources of data (i.e., videotaped structured interviews, questionnaires, Informal Reading Inventories, cued-recall interviews, informal conversations with students, teachers and parents, and document review) recorded how they approached reading tasks through observations of reading episodes at home, school and in the community. Overall, case study findings provided important information regarding ASL signing Deaf readers' opinions about the value or purposes of reading while living within the Deaf and Hearing worlds. Participants valued reading and used reading and writing to interface Deaf and Hearing cultures. Converging evidence revealed how participants used both ASL and English as tools for building comprehension and decoding while reading. Contrary to the literature, findings reflected how these two Deaf high school students were active, strategic readers.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".