Sign language ideologies: Practices and politics
Bibliographic record
Abstract
While much research has taken place on language attitudes and ideologies regarding spoken languages, research that investigates sign language ideologies and names them as such is only just emerging.Actually, earlier work in Deaf Studies and sign language research uncovered the existence and power of language ideologies without explicitly using this term.However, it is only quite recently that scholars have begun to explicitly focus on sign language ideologies, conceptualized as such, as a field of study.To the best of our knowledge, this is the first edited volume to do so.Influenced by our backgrounds in anthropology and applied linguistics, in this volume we bring together research that addresses sign language ideologies in practice.In other words, this book highlights the importance of examining language ideologies as they unfold on the ground, undergirded by the premise that what we think that language can do (ideology) is related to what we do with language (practice).¹All the chapters address the tangled confluence of sign language ideologies as they influence, manifest in, and are challenged by communicative practices.Contextual analysis shows that language ideologies are often situation-dependent and indeed often seemingly contradictory, varying across space and moments in time.Therefore, rather than only identifying language ideologies as they appear in metalinguistic discourses, the authors in this book analyse how everyday language practices implicitly or explicitly involve ideas about those practices and the other way around.We locate ideologies about sign languages and communicative practices, which may not be one and the same, in their contexts, situating them within social settings, institutions, and historical processes, and investigating how they are related to political-economic interests as well as affective and intersubjective dynamics.Sign languages are minority languages using the visual-kinesthetic and tactile-kinesthetic modalities.It is important to recognize both that the affordances of these modalities are different from those of the auditory-oral (spoken) modality, and that signers, like speakers, often make use of multilingual and multimodal 1 This assertion is indebted to the work of Silverstein and Hanks, among others.See for example
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".