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Record W4304184965 · doi:10.7592/ejhr.2022.10.3.625

Humor in conversation among bilinguals

2022· article· en· W4304184965 on OpenAlexaboutno aff
Marianthi Georgalidou, Vasilia Kourtis-Kazoullis, Hasan Kaili

Bibliographic record

VenueEuropean Journal of Humour Research · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsConversationTurkishEthnic groupLinguisticsPragmaticsEthnographyFocus (optics)Identity (music)Neuroscience of multilingualismSociologyPsychologyMultilingualismSocial identity theorySocial groupSocial psychologyAnthropologyAestheticsArtPhilosophy

Abstract

fetched live from OpenAlex

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.”

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.194
GPT teacher head0.376
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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