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Record W2905505886 · doi:10.17705/1jais.00521

Theorizing the Multilevel Effects of Interruptions and the Role of Communication Technology

2018· article· en· W2905505886 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Association for Information Systems · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsMcGill UniversityQueen's University
Fundersnot available
KeywordsAffect (linguistics)PsychologyMultilevel modelSocial psychologyWork (physics)Knowledge managementComputer scienceCognitive psychologyEngineeringCommunication

Abstract

fetched live from OpenAlex

Our understanding of how interrupting the work of an individual affects group outcomes and the role of communication technologies (CT) in shaping these effects is limited. Drawing upon coordination theory and the literatures on computer-mediated communication and interruptions, this paper develops a multilevel theory of work interruptions. It suggests that interruptions that target individuals can also affect other group members through various ripple effects and a cross-level direct effect. We also discuss how the usage of five CT capabilities during interruption episodes can moderate the impact of interruptions at the individual and group levels. Our theoretical model draws attention to the importance of examining the individual-to-group processes to better understand the impact of interruptions in group environments. Additionally, by accounting for the role of the use of CT capabilities during interruption episodes, our work contributes to both the interruptions literature, which dedicates scant attention to the interrupting media, and to IS research on media use and media effects.

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.

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)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
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 science0.0010.000
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 head0.056
GPT teacher head0.368
Teacher spread0.312 · 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