MétaCan
Menu
Back to cohort
Record W2143087028 · doi:10.1109/re.2008.26

Information Brokers in Requirement-Dependency Social Networks

2008· article· en· W2143087028 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsInterdependenceInformation flowDisseminationKnowledge managementDependency (UML)Computer scienceKnowledge flowProcess managementRequirements analysisInformation systemBusinessEngineering

Abstract

fetched live from OpenAlex

Requirements interdependencies create technical dependencies among project members that generally belong to different functional groups in an organization, but who need to coordinate activities during processes of requirements change management. Effective knowledge management is needed to disseminate information on requirement changes across teams working on interdependent requirements to avoid mis-interpretations. Social networks are regarded as important in fostering knowledge management, where brokers or gatekeepers have the role of project members facilitating information flow. However, little is known about processes of information flow and brokerage in social networks built around interdependent requirements. In a field study of requirement interdependencies in a large IT manufacturing organization, we found that brokers holding pockets of knowledge have an impact on information flow in requirement-interdependent teams. We discuss a number of patterns of information flow and draw implications for processes of requirements change management.

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: Methods · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.208

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 communication0.0000.002
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 head0.020
GPT teacher head0.246
Teacher spread0.226 · 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