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Record W2076604500 · doi:10.5296/ijl.v5i3.3900

Canadian and Cameroonian English-Speaking University Students’ Compliment Strategies

2013· article· en· W2076604500 on OpenAlexaffabout
Bernard Mulo Farenkia

Bibliographic record

VenueInternational Journal of Linguistics · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsCape Breton University
Fundersnot available
KeywordsSituational ethicsPsychologyLinguisticsPreferenceSociologySocial psychologyMathematicsPhilosophy

Abstract

fetched live from OpenAlex

This paper addressees compliment strategies in two regional varieties of English, namely Cameroon English and Canadian English. Data were collected through written Discourse Completion Tasks with 25 Canadian and 25 Cameroonian University students. The study examines similarities and differences between the two groups with regards to move structure and the head act strategies, the use of lexical and syntactic / stylistic devices and the use of supportive moves in six different situations. It was found that the Cameroonians show a very strong preference for single heads whereas the Canadians mostly favor multiple heads and that the Cameroonians use indirect compliments much more than the Canadians. The results reveal that the Canadians employ more lexical elements (adjectives, adverbs, verbs) than the Cameroonians. With regard to external modification of the core compliments, the findings suggest that the Canadians use much more supportive moves, i.e. pre-compliments and post-compliments, than the Cameroonians. Some differences were also found with regard to the situational distribution and types of internal and external modification devices.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.282
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations5
Published2013
Admission routes2
Has abstractyes

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