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Ad Hoc Virtual Teams

2002· book-chapter· en· W1537788425 on OpenAlex
Guy Paré, Line Dubé

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

VenueIGI Global eBooks · 2002
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicCollaboration in agile enterprises
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsVirtual teamThe InternetCollaborative softwareVideoconferencingInformation and Communications TechnologyKnowledge managementInstant messagingWorld Wide WebEmerging technologiesBusinessComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Virtual arrangements are proposed as a way for organizations to face the challenges of the upcoming century and to operate both efficiently and innovatively (Bleecker, 1994; Jarvenpaa & Ives, 1994). Information and communication technologies (ICT) serve as powerful enablers of virtual organizing in the form of various intra- and inter-firm arrangements (Knoll & Jarvenpaa, 1995). Among other emerging arrangements, virtual teams, both within and across organizations, are relatively recent phenomena brought about in part by the emergence of technologies such as electronic mail, Internet, groupware and videoconferencing (Barnatt, 1995; Iacono & Weisband, 1997; Lipnack & Stamps, 1997). The reluctance of many workers to relocate for a new job, the global nature of the marketplace, the need to complete projects as quickly as possible, and the need to tap the best brains no matter where they may be, are all examples of drivers of virtual teams within and across organizations (Geber, 1995; Duarte & Snyder, 1999; Lipnack & Stamps, 1997).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.802
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.007

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 head0.013
GPT teacher head0.218
Teacher spread0.204 · 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