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Record W2406365666 · doi:10.29173/cais612

Too Much to Handle? Take Advantage of Working across Multiple Virtual Team Projects

2013· article· fr· W2406365666 on OpenAlexaffvenue
Lu Xiao

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2013
Typearticle
Languagefr
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsHuman multitaskingVirtual teamRepriseHumanitiesPolitical scienceKnowledge managementPsychologyComputer scienceArt

Abstract

fetched live from OpenAlex

Fast-forming, fast-dissolving virtual teams have become an important part of the modern organizational life. Managing multiple group projects in the groupware environment is therefore increasingly becoming significant. Prior studies have focused on the negative effects caused by multitasking such as interruption handling and work resumption. In this paper, we discuss the potential positive effects of working across multiple virtual team projects aiming at provoking research directions about management of multiple virtual team projects through collaborative technologies.Les équipes virtuelles éphémères sont une part importante de la vie moderne en entreprise et la gestion de projets de groupe au moyen de collecticiels devient de plus en plus significative. Les études antérieures ont étudié l’effet négatif du fonctionnement multitâche, notamment l’interruption et la reprise des travaux. Dans cette communication, on discute des effets positifs potentiels de travailler au sein de différentes équipes virtuelles dans le but de dégager un axe de recherche sur la gestion de projets de groupe au moyen de technologies collaboratives.

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)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0060.021
Open science0.0040.002
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 head0.354
Teacher spread0.212 · 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

Citations0
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSISame topicPersonal Information Management and User BehaviorFrench-language works237,207