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Record W2618978265 · doi:10.1145/3047273.3047352

Towards a Context-based Citizen Participation Approach

2017· article· en· W2618978265 on OpenAlexafffund
Amal Marzouki, Sehl Mellouli, Sylvie Daniel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsUniversité Laval
FundersCanadian Internet Registration Authority
KeywordsTypologyContext (archaeology)Relevance (law)Multidisciplinary approache-participationRepresentation (politics)Knowledge managementValue (mathematics)Public relationsAnalyticsSociologyComputer scienceData sciencePolitical scienceSocial sciencePolitics

Abstract

fetched live from OpenAlex

Governments are more and more adopting Citizens' participation processes since they may help better understand needs and better reach communities' goals. With the emergence of ICTs, citizens' participation processes took new forms such as social media, blogs and participative platforms. Nevertheless, although citizens' participation outstands a great value for governments, its implementation raises several issues. Based on a review of the literature, this paper identifies a typology of issues regarding the implementation of CP processes. This paper is an attempt to open new research avenues on citizens' participation through the multidisciplinary typology of issues it proposes. As well, drawing on two categories of issues (citizens' and technology issues), a context-based citizen participation approach is proposed that is based on three main concepts: context-based reasoning, spatio-temporal representation, and visual analytics. Further empirical studies need to be established to assert the relevance of the proposed approach.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.362
Teacher spread0.282 · 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.

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

Citations12
Published2017
Admission routes2
Has abstractyes

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