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Record W1565004988 · doi:10.15353/joci.v11i2.2839

Communities in Context: Taking Control of Their Tools in Common(s)

2015· article· en· W1565004988 on OpenAlexvenueno aff
Aldo de Moor

Bibliographic record

VenueThe Journal of Community Informatics · 2015
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsCommonsDeclarationCorporate governanceThe InternetContext (archaeology)Internet governanceControl (management)Computer scienceFrame (networking)Knowledge managementPublic relationsPolitical scienceBusinessWorld Wide WebTelecommunicationsLawArtificial intelligence

Abstract

fetched live from OpenAlex

In this exploratory paper, we outline some issues of inter-community socio-technical systems governance. Our purpose here is not to solve these issues, but to raise awareness about the complexity of socio-technical governance issues encountered in practice. We aim to expand on the rather abstract definition of community-based Internet governance as proposed in the Internet for the Common Good Declaration, exploring how it plays out in practice in actual collaborating communities. We introduce a simple conceptual model to frame these issues and illustrate them with a concrete case: the drafting and signing of the declaration. We show some of the shortcomings of and socio-technical fixes for Internet collaboration support in this particular case. We end this paper with a discussion on directions for strengthening the collaboration commons.

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)0.041
metaresearch head score (Gemma)0.051
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.051
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0100.039
Scholarly communication0.0220.040
Open science0.0040.031
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.098
GPT teacher head0.309
Teacher spread0.211 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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