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Record W7047892178

Humour in meetings: A study of power and solidarity in the Malaysian academic context / Nor Azikin Mohd Omar

2012· other· en· W7047892178 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Malaya Students Repository · 2012
Typeother
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsSolidarityMalayEthnic groupPower (physics)Transcription (linguistics)Context (archaeology)Notation
DOInot available

Abstract

fetched live from OpenAlex

This study examines the linguistic features that describe the functions of humour associated with power and solidarity in a particular workplace settings referred to as NAS. The purpose of this study is to investigate the nature of humour that is manifested in tandem with the concept of power and solidarity in symmetrical and asymmetrical positions during academic management meetings. Moreover, the aim of the study is to ascertain the turn taking patterns accompanying humour in these respective meetings. The parameters of this study are confined to the different rankings of the participants who utilise humour either to be used for exercising power or building rapport in a hierarchical environment. The data were recorded from four semiformal meetings at NAS with a total combination of 380 minutes and 189 seconds duration of time. Although the medium of instruction was primarily English Language, it was discovered that code switching in Malay occurred throughout the meetings. The age range of the participants ranged from 24-55 years old and they are all proficient in the English Language. The dominant ethnicity of the participants is Malay while there were only two participants who are Chinese and a native speaker of English from Canada. All the four meetings were transcribed using Jariah Mohd Jan’s (1999) transcription notation which was adapted from Jefferson’s (1978) conventions. The adapted transcription highlights the distribution of turns between speakers, occurrences of interruptions and the point when the prior speaker finishes his/her contribution in relation to the next speaker’s turn (Jariah Mohd Jan, 1999:226). The instances of humour were categorised using Hay’s Taxonomy of Functions of Humour (1995) which mainly focuses on the two functions which are power and solidarity. The organisation of turn taking accompanying humour was analysed based on Sacks et al. Turn-Taking Model (1974). The findings revealed that teasing was the most popular function of humour in the power and solidarity category. Teasing was the predominant strategy utilised by the academicians to enact power or to maintain camaraderie among the team members. On the other hand, conflict was the least popular type of humour that was associated with power play and share was the lowest type of humour produced by the participants which functioned as rapport building. The data suggested that the organisation of turns which subsumed humour were basically adhering to the second rule of SSJ Model of Turn-Taking (1974). The rule demonstrated that turns were taken through self-selection where the members of the floor will select themselves in order to make their respective contributions. This rule was discovered as the most applied rule by the participants especially for those in higher status in their attempt to produce humour. This study provides great insights that the production of humour in academic management meetings is influenced by the status or position that one occupies. Moreover, this study will certainly contribute to the existing body of local researches as well as it could be used to extend on future studies on power and solidarity in relation to production of humour.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.985

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

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