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Record W2080368628 · doi:10.1145/1082983.1083116

Cultural patterns in software process mishaps

2005· article· en· W2080368628 on OpenAlexaffabout
Eve MacGregor, Yvonne Hsieh, Philippe Kruchten

Bibliographic record

VenueACM SIGSOFT Software Engineering Notes · 2005
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsExploratory researchProcess (computing)Phase (matter)Engineering ethicsSociologySoftwareGrounded theoryManagement scienceComputer scienceQualitative researchEngineeringSocial science

Abstract

fetched live from OpenAlex

This paper describes a current and ongoing research project being conducted at the University of British Columbia, Canada. The paper begins by briefly describing past anthropological and sociological culture research. This research will inform our current exploration into the issues surrounding culture and its role in Global Software Development efforts. It then clarifies why this research is particularly important. The paper continues with a description of the current phase of this research, which is an exploratory qualitative approach rooted in Grounded Theory, and of the next phase, which will be a more quantitative approach looking at specific "problem areas" that were identified during the first phase.

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)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0040.005
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.273
Teacher spread0.255 · 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 designQualitative
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

Citations61
Published2005
Admission routes2
Has abstractyes

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