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Record W1675703028 · doi:10.15353/joci.v11i2.2831

Sensitizing concepts for the next community-oriented technologies: shifting focus from social networking to convivial artifacts

2015· article· en· W1675703028 on OpenAlexvenueno aff
Federico Cabitza, Carla Simone, Denise Cornetta

Bibliographic record

VenueThe Journal of Community Informatics · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsAffordanceComputer scienceOpenness to experienceSet (abstract data type)Field (mathematics)Focus (optics)Community networkHuman–computer interactionData scienceKnowledge managementWorld Wide WebPsychologyMathematics

Abstract

fetched live from OpenAlex

This paper proposes a set of sensitizing concepts for the evolution of technologies supporting both online and hybrid communities. These concepts regard the affordances that a network community and its technological infrastructure should offer to its members, grounding and extending the notion of network communities and the related concepts proposed in the literature; in particular, we focus on the community affordance we denote as conviviality, and discuss it in light of several previous research contributions to see it as an important facet of community interaction that should orient the design of its enabling technology. To this aim, the paper also proposes an initial set of three principles that should inform the design of convivial artifacts, namely bounded openness, collaboration-orientedness and selective inclusiveness, and illustrate them with some examples as further sensitizing concepts for the Communities & Technologies field.

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)0.012
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0040.044
Scholarly communication0.0110.019
Open science0.0020.011
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.134
GPT teacher head0.309
Teacher spread0.175 · 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 designTheoretical or conceptual
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

Citations21
Published2015
Admission routes1
Has abstractyes

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