Theory of ecology of pressures as a tool for classifying language shift in bilingual communities
Bibliographic record
Abstract
Abstract This article examines the stage of language shift in Tlaxco (Santiago Tlaxco), a bilingual Nahuatl-Spanish-speaking community in Puebla, Mexico. We employ the theory of ecology of pressure framework to identify and analyze the pressures that favor or deter language maintenance of Nahuatl and categorize the level of language shift. The research data were drawn from 207 completed census questionnaires in 50 homes. Our findings show that Nahuatl is vigorous and used in the home and the community. Nahuatl is the preferred language of communication with adults and the older generation, while Spanish is commonly used with and among the youth. Based on these results, we conclude that Nahuatl continues to thrive in the community, with the risk of Spanish gradually replacing Nahuatl as the preferred language of communication across all age groups if the current youth population does not follow the current language use pattern as they enter adulthood. This study is one of the first to analyze the sociolinguistic situation of Tlaxco (Santiago Tlaxco). The findings, which are discussed in conjunction with other qualitative and observational studies, also provide a snapshot of a community at the potential early stage of language shift.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".