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Record W1514202727 · doi:10.15353/joci.v9i1.3191

Supporting End User Development in Community Computing: Requirements, Opportunities, and Challenges

2012· article· en· W1514202727 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Journal of Community Informatics · 2012
Typearticle
Languageen
FieldComputer Science
TopicSpreadsheets and End-User Computing
Canadian institutionsnot available
Fundersnot available
KeywordsEnd-user developmentAutonomyContext (archaeology)Computer scienceSituatedDomain (mathematical analysis)Knowledge managementData scienceEnd userWorld Wide WebArtificial intelligencePolitical scienceMathematics

Abstract

fetched live from OpenAlex

End user development (EUD) tools in community computing are not well-developed and typically do not take into consideration the unique characteristics of community groups such as lack of human, financial, and technological resources. Using a case study, we explore EUD in the domain of community computing. Situated in community computing context, we identify design requirements of EUD tools, demonstrate the use of conceptual scaffolds to support EUD, and illustrate the need of new evaluation methods of EUD tools. We discuss the tension between pushing EUD tools to community computing for local autonomy on technology issues and the long time practice of seeking and relying on external technical expertise. We call for research studies that address the tension and explore ways of creating and stimulating “pull” force from the community groups.

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)0.015
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0020.002
Research integrity0.0000.001
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 head0.188
GPT teacher head0.325
Teacher spread0.137 · 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