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Record W2097177877 · doi:10.1109/isre.2001.948552

An empirical study of facilitation of computer-mediated distributed requirements negotiations

2002· article· en· W2097177877 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFacilitationFacilitatorNegotiationKnowledge managementEmpirical researchCollaborative softwareSocial facilitationComputer sciencePsychologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Group facilitation is an important element of group approaches to requirements engineering (RE). The facilitation in traditional face-to-face groups is challenged by the increased globalization of the software industry. Thorough empirical investigation of human facilitation in computer-mediated requirements meetings is needed. This paper presents findings about the facilitation of distributed group settings in a controlled environment. Three professional facilitators mediate 15 three-person groups negotiating software requirements. Facilitation in face-to-face meetings is contrasted with four group settings in which the facilitator is physically separated from the group or co-located with key stakeholders. Rich qualitative and behavioral data enables an understanding of differences and similarities in the facilitation of the distributed groups and of aspects that were detrimental or beneficial to their facilitation. The empirical evidence indicates a reduced richness of social behaviors in computer-mediated group settings which: made the group facilitation problematic; but also enabled certain facilitation support in the medium itself.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.063
GPT teacher head0.334
Teacher spread0.272 · 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