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Record W4249542458 · doi:10.1108/9781786354495

Extreme Teaming

2017· book· en· W4249542458 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
Typebook
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Today’s global enterprises increasingly involve collaborative work by teams of experts operating across different professions, organizations, and industries. Extreme Teaming provides new insights into the world of complex, cross industry projects and the ways they must be managed.. Leading experts Amy Edmondson and Jean-Franois Harvey analyze contemporary cases that expose the complex demands of cross-boundary collaboration on management, and inform our understanding of teams. Containing powerful insights and practical guidelines that allow managers to bridge professional divides and organizational boundaries in order to work together effectively, this is a new exploration of the challenges involved in today’s global enterprises.. The authors demonstrate that the work done in the modern organization is less and less about looking inward and creating strong teams inside the company, and more about teaming across boundaries – that often are in flux.. Extreme Teaming is a must-read book for all courses related to leading open innovation; teamwork and collaboration; project management; and cross-boundary work.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.377
Threshold uncertainty score0.580

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 science0.0020.000
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 head0.049
GPT teacher head0.270
Teacher spread0.221 · 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