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Record W2061889093 · doi:10.5430/jbar.v2n1p66

What are the Features and Practices of Workgroups that Epitomize Cohesion: Development of a Preliminary Measure

2013· article· en· W2061889093 on OpenAlexvenueno aff
Kathryn von Treuer, Matthew Fuller‐Tyszkiewicz, Simon Moss, Janet McLeod, Sigrid M. Hamilton

Bibliographic record

VenueJournal of Business Administration Research · 2013
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)PrideGroup cohesivenessFeelingPsychologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Presently, no consensus has been reached with regards to measuring workplace cohesion. Cohesion measures often allude to abstract concepts rather than tangible features, therefore this study identified the tangible features and specific practices that epitomize cohesive workgroups. Specifically, 28 individuals were interviewed and asked to reflect upon two workgroups in which they had been employed before, only one of which was cohesive. Participants identified tangible features, practices, or characteristics that typified each of these workgroups. Content analysis uncovered 14 features of cohesion, such as shared emotional events in the past, friendly and welcoming greetings, and a feeling of pride when other people in the team excel on some task. A provisional measure of cohesion was then distilled from these items.

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)0.002
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 score0.541
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.142
GPT teacher head0.423
Teacher spread0.282 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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