Usted es haragan pero vos sos lazy: initialization in Honduran Sign Language
Bibliographic record
Abstract
Initialization, an outcome of language contact common to signed languages, has become a global phenomenon. I define initialization as the incorporation of the orthography of a word of a dominant spoken language via the cultural construct of a manual orthography into signs with a semantic correspondence to that word. Despite its being very common within (relatively) well-documented sign languages such as American Sign Language (Padden & Brentari, 2001), Australian Sign Language (Schembri & Johnston, 2007) and Québec Sign Language (Machabée, 1995), the literature on the subject is very small. To assist in expanding the nascent fields of sociolinguistics and anthropology of Deaf communities, ethnographic research involving primarily corpus building, interviews and participant observation was performed within the Deaf community of central Honduras to offer preliminary insights into how the personal and group identities of the Honduran Deaf are negotiated through linguistic interactions. Variable initialization is quite a salient marker because of its use in the diverging sociolects of Deaf Honduras. This poses the questions: what instances of variable initialization exist in the community; how are these variable forms manipulated to construct identities; how does variant initialization mark social differentiation in the community? How are linguistic variation and social differentiation intertwined? Social relationships and individual identity are studied by means of this linguistic marker as language is used to build social meaning. In particular, I argue that linguistic variation is polarizing as variant initialization is used to both reflect and justify the social division of the community into central and peripheral.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".