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Record W2884680550 · doi:10.20360/langandlit29406

The LinkVan Project: Participatory Technology Design in Vancouver

2018· article· en· W2884680550 on OpenAlexafffundvenueabout
Suzanne Smythe, Dionne Pelan, Sherry Breshears

Bibliographic record

VenueLanguage and Literacy · 2018
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaSimon Fraser University
KeywordsDowntownCitizen journalismSociologyLiteracyDirectoryParticipatory designDigital literacyMedia studiesPublic relationsWorld Wide WebLibrary sciencePolitical sciencePedagogyComputer scienceEngineeringGeography

Abstract

fetched live from OpenAlex

This article tells the story of “LinkVan,” a project that explores approaches to participatory technology design to forge more equitable digital and social relations in the Downtown Eastside (DTES) community of Vancouver, British Columbia. LinkVan began as a project to create a literacy-friendly online service directory for low-income and homeless citizens. We trace the experiences and patterns of digital inequality that led to the formation of the project and describe the evolving approach to technology design oriented to “the direct involvement of people in the co-design of the technologies they use” (Simonsen & Robertson, 2013 p. 2). We consider insights from 58 user experience interviews that suggest the precariousness of access, the centrality of digital literacy education in participatory technology design, and the potential of side-by-side ‘conversations at the interface’ (Attar, 2005; Barbatsis, Comacho, & Jackson, 2004) to imagine new digital landscapes and new social relations.

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 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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.325
Teacher spread0.301 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations2
Published2018
Admission routes4
Has abstractyes

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