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Record W2157010671 · doi:10.1177/1742766509348672

Can the use of digital media favour citizen involvement?

2009· article· en· W2157010671 on OpenAlexaffabout
Serge Proulx

Bibliographic record

VenueGlobal Media and Communication · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSummitCivil societyPoliticsInformation societyPublic relationsContext (archaeology)SociologyICTSPolitical scienceDigital divideSocial mediaSocial movementInformation and Communications TechnologyMedia studiesLaw

Abstract

fetched live from OpenAlex

We present here the results of recent studies on the emergence in Quebec of associations of a new kind, which we call technology activist groups. These groups consist of individuals who, on the basis of their own expertise in computer programming or in establishing specialist technological structures (WiFi hotspots), are developing social practices involving information technologies (ICTs). We try to give some elements of a response to some specific questions such as: What effects are these technology activists having on the dynamics of community activism in Quebec? In a broader context, at the level of political imagination in today’s societies, how far can these technical activist groups act politically to help redefine the project of the coming ‘information society’? And conversely, can the project of a ‘knowledge-sharing society’ — as formulated by the representatives of civil society organizations at the WSIS (World Summit on the Information Society) in Tunis — help to redefine the aims and actions of actors in community politics?

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)0.007
metaresearch head score (Gemma)0.022
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: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.008
Scholarly communication0.0100.006
Open science0.0010.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0180.001

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 head0.068
GPT teacher head0.303
Teacher spread0.235 · 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

Citations11
Published2009
Admission routes2
Has abstractyes

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