MétaCan
Menu
Back to cohort
Record W2100989189 · doi:10.1109/enabl.2003.1231398

Assessing collaborative tools from an information-processing perspective: identification of value-added processes

2004· article· en· W2100989189 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
FieldBusiness, Management and Accounting
TopicCompetitive and Knowledge Intelligence
Canadian institutionsMcGill University
Fundersnot available
KeywordsTeamworkRelevance (law)Perspective (graphical)Computer scienceIdentification (biology)Value (mathematics)Collaborative softwareKnowledge managementAdded valueData scienceArtificial intelligenceMachine learningManagement

Abstract

fetched live from OpenAlex

The authors explore the relevance of an information-processing perspective to collaboration. Based on the information cycle and inspired by the mechanics of collaboration, their model suggests that collaboration implies two types of informational activities: taskwork-related and teamwork-related. They present competitive intelligence as an example of collaborative projects, and CI taskwork informational mechanics, translated into criteria, to evaluate CI software. These criteria reveal the value-added processes that must be incorporated in a tool to transform information into intelligence. To assess the collaborative utility of CI tools, the paper suggests a number of teamwork informational mechanics that could be used to define another level of evaluation criteria.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.018
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 head0.028
GPT teacher head0.313
Teacher spread0.285 · 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

Quick stats

Citations7
Published2004
Admission routes1
Has abstractyes

Explore more

Same topicCompetitive and Knowledge IntelligenceFrench-language works237,207