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Record W2158049446 · doi:10.1145/966221.966224

Global software development

2003· article· en· W2158049446 on OpenAlexafffund
Filippo Lanubile, Daniela Damian, Heather L. Oppenheimer

Bibliographic record

VenueACM SIGSOFT Software Engineering Notes · 2003
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversity of Victoria
FundersVictoria UniversityUniversity of VictoriaCarnegie Mellon University
KeywordsSoftware engineeringSoftware developmentEngineeringEngineering managementSoftwareSoftware peer reviewLibrary scienceComputer scienceSoftware construction

Abstract

fetched live from OpenAlex

The International Workshop on Global Software Development was held in Portland (Oregon, USA) on May 9 2003, as part of the International Conference on Software Engineering 2003. A multicultural group of twenty-five people contributed to a successful workshop that debated the continued challenges of software development in global teams. The workshop consisted of an invited talk, sixteen short presentations, and fruitful discussions. We present an overview of the workshop motivation and then focus on the workshop's technical program. The workshop web site, including papers and slides, can be found at .

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0630.017

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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations85
Published2003
Admission routes2
Has abstractyes

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