American Sign Language and Early Literacy: A Model Parent-Child Program
Bibliographic record
Abstract
The usual definition of the term literacy generally corresponds with mastering the reading and writing of a spoken language. This narrow scope often engenders unsubstantiated claims that print literacy alone leads to, among other so-called higher-order thinking skills, logical and rational thinking and the abstract use of language. Thus, the importance of literacy for deaf children in Sign Language (ASL) is marginalized, asserts author Kristin Snoddon in her new book American Sign Language and Early Literacy: A Model Parent-Child Program. As a contrast, Snoddon describes conducting an ethnographic, action study of the ASL Parent-Child Mother Goose program, provided by a Deaf service agency in Ontario, Canada to teach ASL literacy to deaf children. According to current scholarship, literacy is achieved through primary discourse shared with parents and other intimates, which establishes a child s initial sense of identity, culture, and vernacular language. Secondary discourse derives from outside agents and interaction, such as expanding an individual s literacy to other languages. Snoddon writes that the focus of the ASL Parent-Child Mother Goose program is on teaching ASL through rhymes and stories and some facets of the culture of Deaf ASL users. This focus enabled hearing parents to impart first-language acquisition and socialization to their deaf children in a more natural primary discourse as if the parents were Deaf themselves. At the same time, hearing parents experience secondary discourses through their exposure to ASL and Deaf culture. Snoddon also comments on current infant hearing screening and early intervention and the gaps in these services. She discusses gatekeeper individuals and institutions that restrict access to ASL for young Deaf children and their Finally, she reports on public resources for supporting ASL literacy and the implications of her findings regarding the benefits of early ASL literacy programming for Deaf children and their families.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".