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Record W2472152857 · doi:10.1287/isre.2016.0646

Folding and Unfolding: Balancing Openness and Transparency in Open Source Communities

2016· article· en· W2472152857 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

VenueInformation Systems Research · 2016
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsMcGill University
Fundersnot available
KeywordsTransparency (behavior)Openness to experienceComputer scienceOpen dataComputer securityWorld Wide WebPsychologySocial psychology

Abstract

fetched live from OpenAlex

Open source communities rely on the espoused premise of complete openness and transparency of source code and development process. Yet, openness and transparency at times need to be balanced out with moments of less open and transparent work. Through our detailed study of Linux Kernel development, we build a theory that explains that transparency and openness are nuanced and changing qualities that certain developers manage as they use multiple digital technologies and create, in moments of needs, more opaque and closed digital spaces of work. We refer to these spaces as digital folds. Our paper contributes to the extant literature by providing a process theory of how transparency and openness are balanced with opacity and closure in open source communities according to the needs of the development work; by conceptualizing the nature of digital folds and their role in providing quiet spaces of work; and, by articulating how the process of digital folding and unfolding is made far more possible by select elite actors’ navigating the line between the pragmatics of coding and the accepted ideology of openness and transparency.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.008
Open science0.0010.001
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 head0.107
GPT teacher head0.366
Teacher spread0.259 · 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