Language Choice and Family Language Policy in Inter-Ethnic Marriages in South-Eastern Nigeria
Bibliographic record
Abstract
Ensuring continuity in the intergenerational transmission of language is a crucial element in the process of its maintenance (Fishman,1991). The family has been identified as the bedrock of such social transmission thus raising questions about language choice which usually ignites emotional reactions especially in inter-ethnic marriages. This paper investigates the issue of language socialization and language choice in inter-ethnic marriages from a macro-sociolinguistic perspective involving the intersection of Efik-Ibibio, Igbo and Lokaa couples and children who are products of these unions, given that parents make decisions with regard to the family linguistic choices and children are the agents of socialization and change in language ecology and family dynamics. The study is rooted in Hyme's (1962) theory of ethnography of speaking which is concerned with the linguistic resources people use in context and the socially situated uses and meaning of language; what language to use in what place, to whom and upon what occasion etc and Giles' (1979) socio-psychological theory of accommodation which seeks to explain cognitive adjustments in the choice of language adopted by children. The study discovers that the motivation for indigenous language transmission is weaned as the family does not provide the bond to foster sufficient indigenous languages activities, therefore, children raised in inter-ethnic marriages are not balanced bilinguals. The study has implications for language shift and maintenance in Nigeria. Key words : Language choice; Inter-ethnic marriages; Code-mixing/switching; Linguistic ecology; Multilingualism; Family language policy
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".