Deafness and sign language in a Yucatec Maya community: Emergent Ethnographic Practice
Bibliographic record
Abstract
This paper outlines the potential that community‐based, family‐oriented research strategies have for generating inclusive and sustainable local social programs. Examples drawn from long‐term fieldwork in an indigenous Mayan‐speaking community in Yucatán, Mexico highlight the utility of aligning ethnographic evaluations with available state resources in appropriate and holistic ways. There is a high percentage of deafness in the community of Chican, and a nondiscriminatory attitude toward sign language use that enables the involvement of deaf persons into everyday life activities. In Chican, deafness represents a positive constitutive feature of community identity; the locally developed Yucatec Mayan Sign Language is widely used among both deaf and hearing persons enabling for the inclusion of deaf persons in community life. However, disjuncture between local and state approaches toward community wellbeing are apparent in that state conceptualizations of deafness as a disabling condition, and indigenous identity as being problematic, contrast sharply with local understandings. Through carrying out in depth participant‐observation, I assumed the role I was assigned within community life, and thereby gained insight into local understanding of deafness, communication, and identity. Engaging with children, adolescents, extended family, and community leaders, I participated with family members across age and gender lines in their customary daily activities. By these means, I realized that external perceptions of Chican, concentrating primarily on the presence of deafness in the community, were overshadowing more pressing and generalized community needs. To facilitate local communications with state and humanitarian agencies, I founded a nonprofit organization called “YUCAN Make a Difference A.C.,” which envisions ethnographic practice as a pivotal force in generating mutually rewarding programs of social assistance. [applied anthropology, deafness and sign language, Yucatec Maya, ethnographic practice, nonprofit organizations]
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".