Humour in meetings: A study of power and solidarity in the Malaysian academic context / Nor Azikin Mohd Omar
Bibliographic record
Abstract
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".