Humor in conversation among bilinguals
Bibliographic record
Abstract
In this study, we analyse conversations recorded during ethnographic research in two bilingual communities on the island of Rhodes, Greece. We examine: (a) the bilingual in Greek and Turkish Muslim community of Rhodes (Georgalidou et al. 2010, 2013) and (b) the Greek-American/Canadian community of repatriated emigrant families of Rhodian origin (Kourtis-Kazoullis 2016). In particular, combining interactional and conversation analytic frameworks (Auer 1995; Gafaranga 2007), we examine contemporary approaches to bi-/multilingualism focusing on the pragmatics of humour in conversations among bilinguals. We scrutinise aspects of the overall and sequential organisation of talk as well as instances of humour produced by speakers of different ethnic origin, generation, and social groups. We focus on the construction of “otherness,” which reflects the dynamic interplay between the micro-level of conversational practices and the macro-level of discourse involving contrasting categorisations and identities pertaining to differently orientated ethnic and social groups. Based on the analysis, we will show a) how humorous targeting orients in-groups versus out-groups, and b) mediates the dynamic process of constructing the identity of speakers who, being members of minority linguistic communities, represent “otherness.”
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".