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Record W2338729281 · doi:10.1037/10690-009

The importance of awareness for team cognition in distributed collaboration.

2004· book-chapter· en· W2338729281 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

VenueAmerican Psychological Association eBooks · 2004
Typebook-chapter
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsUniversity of CalgaryUniversity of Saskatchewan
Fundersnot available
KeywordsSocially distributed cognitionCognitionPsychologyKnowledge managementCognitive scienceComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

Although the phrase team cognition suggests something that happens inside people's heads, teams are very much situated in the real world, and there are a number of things that have to happen out in that world for teams to be able to think and work together. This is not just spoken communication. Depending on the circumstances, effective team cognition includes things like using environmental cues to establish a common ground of understanding, seeing who is around and what they are doing, monitoring the state of artefacts in a shared work setting, noticing other people's gestures and what they are referring to, and so on (Clark, 1996; Hutchins, 1996). In this chapter, we will argue that awareness of other group members is a critical building block in the construct of team cognition, and consequently that computational support for awareness in groupware systems is crucial for supporting team cognition in distributed groups. Our main message is that: ... for people to sust

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.335
Teacher spread0.313 · 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