West African Englishes on the Move: New Forms of English as a Lingua Franca (ELF) in Germany : Abschlussbericht
Bibliographic record
Abstract
The project investigates the use of West African varieties of English in lingua franca (ELF) interaction in Germany. The primary database is a corpus of language-biographical interviews – individual and focus-group – with 67 mostly anglophone West African migrants, with a total duration of ca. 55 hours. The corpus is used to describe the types of English used, but also serves as rich source for the study of interviewees’ communicative experiences in migration, their language attitudes and language ideologies. Extracts from the data were used for accent evaluation experiments in which German-speaking listeners rated intelligibility and prestige. The results can be summarised as follows. Occasional problems with each other’s accents notwithstanding, West African Englishes work well in lingua-franca communication between immigrants and the resident population. There is, however, friction in communication in institutional settings – from German as a Foreign Language classrooms to encounters with authorities in administration. Migrants from anglophone postcolonial contexts tended to over-rate the prestige and usefulness of English in the German socio-communicative context. Additional frustration was caused by the fact that multilingual strategies involving code-switching and other forms of language mixing, which served interviewees well in everyday communication, were not equally welcome in institutional settings. A surprising finding was the enormous ethnolinguistic vitality of English-lexifier Pidgin in the West African immigrant community in Germany. Pidgin sheds the residual stigma that attaches to it in the countries of origin and serves as a very strong and positively connoted identity marker in an otherwise very diverse community. The project’s findings support a shift in official language policy towards immigrants. While the acquisition of German remains essential for long-term integration, English should be recognised and valued as a useful transitional lingua franca – both in everyday life and in institutional settings. Successful lingua-franca communication is not necessarily monolingual, but can be effected through multilingual repertoires. The project‘s findings also contribute to international research on varieties of English in migration, as previous work has almost exclusively focussed on English-dominant destination countries such as the US, Canada and the UK. A large portion of the interviews, anonymised audio files and aligned orthographic transcriptions (software: ELAN), will be deposited in a repository hosted by the national Text+ Research Data Infrastructure consortium and be made available for future research on language and migration and the oral history of African migration to Germany in the early 21st century.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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; both teacher heads agree on what is shown here.
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".