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Gossip Has It! An In-Depth Investigation of Malaysian Employees on Gossip Activities at Workplace

2013· article· en· W1541405921 on OpenAlexvenueno aff
Mohd Mursyiddin Abdul Manaf, Erlane K Ghani, Ismie Roha Mohamed Jais

Bibliographic record

VenueCanadian social science · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsnot available
Fundersnot available
KeywordsGossipNonprobability samplingInterpersonal communicationQualitative researchPhenomenonPublic relationsSelection (genetic algorithm)SociologyTheoretical samplingPsychologySocial psychologyComputer scienceSocial sciencePolitical scienceEpistemologyGrounded theory

Abstract

fetched live from OpenAlex

This qualitative study aims at understanding the reasons for conception of gossiping phenomenon among private and public sector employees in Malaysia. Data for this research was gathered through in-depth interviews, which involved 15 informants that had been chosen through purposive sampling, aided by criterion-based selection and being conducted through theoretical sampling. In terms of gossip conception, data from informants have contributed to 8 themes that have been divided into two categories - pertain to content and pertain to functions. From these categories, the researchers conclude that gossip continues to be a firm feature of social and organisational landscapes, whereby without these social activities, interpersonal communication that harnesses the organisational communication would not be able to develop.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.280
Teacher spread0.247 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2013
Admission routes1
Has abstractyes

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