Competition of Ethnic and National Languages within the Home Domain: Insights from Multilingual Sasak Family Language Choice, Lombok – Indonesia
Bibliographic record
Abstract
Competition of languages in a bilingual/multilingual society is a prevalent phenomenon found anywhere in the world. Competition occurs when the choice of one language is supposed to be ‘prioritized’ and ‘prized’ over the other(s) in any domain of language use. This study explores how this phenomenon of language use occurs in the homeland of Sasak vernacular speakers living in the city of Mataram, Lombok–Indonesia. The aim of this study was to investigate the extent to which family members of native Sasak inhabitants in Mataram use their own ethnic language in their daily interaction with their family members in the home, neighborhood, and friendship domains. Data were collected through survey questionnaires, interviews, and participant observations by employing the concept of Fishman’s domain of language use, language attitude, and bilingualism. The obtained data were then selected, classified, and tabulated to compute the frequency of speech occurrences in each study group. The results show that participants displayed positive attitudes towards their mother tongue indicating that they were very proud of their first language. SL was almost always used in daily conversations in the home domain and neighborhood but the rate of use slightly differed among different age, education, and occupational groups. Societal bilingual patterns were portrayed in the stable use of both the indigenous language (SL) in the home domain and the national language (IL) in the official domain in education, government, or religious gatherings. Within the context of EGIDS by SIL, UNESCO developed from Fishman (1972) SL at present is still safe and maintained by its people.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".