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Record W1857070832 · doi:10.15353/joci.v11i3.2697

From Exploration to Design: Aligning Intentionality in Community Informatics Projects

2015· article· en· W1857070832 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 · 2015
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
Fundersnot available
KeywordsIntentionalityParticipatory designGRASPCitizen journalismParticipatory action researchField (mathematics)Management scienceInformaticsExploratory researchTransition (genetics)Computer scienceKnowledge managementEpistemologySociologyEngineering ethicsPolitical scienceEngineeringSocial science

Abstract

fetched live from OpenAlex

This article focuses on a particular aspect of research and design processes in community-based projects: the transition from exploratory stages, concerned with knowledge production, to design stages, in which goals for action-taking are formulated and desired directions for change are envisioned. This paper offers a reflection about the methodological processes that underpin this transition, in response to the questions: How are design goals formulated in community informatics interventions that rely on data-intensive exploratory methodologies, and what factors and dynamics shape them? Guided by these questions, we shed light on various issues related to this transition by recounting and analysing cases taken from field experiences within three different community projects in Syria, Brazil and Mozambique. The article proposes that the transition is associated with shifts in intentionality, which are elusive and hard to grasp, particularly in participatory approaches. Three analytical categories are put forward to illuminate the dynamics of intentionality shifts along the continuum of transitioning from exploration to design. Reflections based on the empirical cases are contributed.

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)0.017
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.398
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.004
Open science0.0050.002
Research integrity0.0000.002
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 head0.226
GPT teacher head0.334
Teacher spread0.107 · 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