Language Change in a Contact Situation: The Case of Slovene in North America
Bibliographic record
Abstract
The article discusses the linguistic situation among immigrants of Slovene descent in the United States of America and Canada. Owing to the geographic distance between Slovenia and the host country and particularly to the very strong influence of the pragmatically dominant English, Slovene there is undergoing a very specific kind of development. Data collected through empirical research (interview excerpts) are analyzed in order to identify contact-motivated changes of Slovene. These are encountered in all types of bilingual discourse (borrowing, code switching, English-influenced monolingual Slovene) and on different linguistic levels from phonology to semantics and pragmatics. The most salient areas of English linguistic impact, however, are morphology with its simplification, regularization and/or even deletion of Slovene inflectional system, and syntax with its gradual adoption of English-like SVO word order patterns. On a sentence level these kinds of structures constitute what could be termed a composite matrix language, made up from the features of both languages. Development, though, stops short of the so-called matrix language turnover (MLT), because it is interrupted by a very rapid process of language shift from Slovene to English. This has been accomplished in the course of three generations in the case of pre-war immigrants and even faster in the case of post-war ones. The variety of Slovene in this particular context is therefore of a very temporary and unstable nature and defies the postulation of rigid structural constraints on it. It nevertheless represents a distinct contact variety of Slovene well worth further research because of the likely insights into the language change mechanisms that it may provide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".