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Record W1985377998 · doi:10.1177/1080569905285543

Building a Shared Virtual Learning Culture

2006· article· en· W1985377998 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBusiness Communication Quarterly · 2006
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeneral partnershipSet (abstract data type)Knowledge managementWorkspaceVideoconferencingBusiness communicationEquity (law)Computer-mediated communicationComputer scienceIntercultural communicationPsychologyMedical educationMultimediaPedagogyBusinessThe InternetWorld Wide WebPolitical science

Abstract

fetched live from OpenAlex

Business professionals increasingly use digital tools to collaborate across multiple cultures, locations, and time zones. Success in this complex environment depends on a shared culture that facilitates the making of knowledge and the best contributions of all team members. To prepare managers for such communication, the authors designed and implemented a semester-long intercultural virtual team project between a management communication course in the United States and one in Canada. To prevent faultlines between subgroups on each campus, the authors set a clear outcome for students’ research, established equity between the two sites, structured assignments so that students worked interdependently across sites”, and encouraged inclusive communication. Faculty considering such a partnership should incorporate a robust collaborative workspace, incorporate preliminary exercises before a large project, provide intensive mentoring and instruction on peer review, arrange for a real visit or videoconference between locations, and expect the project to be both fun and demanding.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.561

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 communication0.0000.000
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 head0.011
GPT teacher head0.281
Teacher spread0.270 · 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