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Online Citizen Consultation and Engagement in Canada

2007· book-chapter· en· W2492340023 on OpenAlexaffabout
Graham Longford, Casey Hurrell

Bibliographic record

VenueIGI Global eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsPolitical sciencePublic administrationDemocracyCivic engagementPoliticsContext (archaeology)Government (linguistics)TurnoutPublic relationsPublic engagementGeographyVotingLaw

Abstract

fetched live from OpenAlex

Like other western liberal democracies, Canada has witnessed the erosion of political participation and civic engagement on the part of its citizens. Recent studies of Canadian democracy have revealed numerous symptoms of malaise, including declines in voter turnout, participation in traditional political institutions, civic literacy, and trust in government (Gidengil, Blais, Nevitte, & Nadeau, 2004; Nevitte, 1996). Governments at the federal, provincial, and municipal levels have launched numerous democratic reform initiatives in response. Along with proposals for electoral and parliamentary system reform, governments in Canada have responded with new citizen consultation initiatives designed to increase public participation in the policymaking process. Incorporating the use of new information and communication technologies (ICTs) into these initiatives, such as online citizen consultation tools, has become a common method used to engage Canadians in the policymaking process. A gradual shift in the language and practice of citizen involvement in the policymaking process has also been taking place, one in which citizen consultation is being complemented by richer and more sustained forms of citizen engagement. This chapter examines the political context and conceptual underpinnings of online citizen consultation and engagement in federal policymaking in Canada, reviews a number of recent examples, and assesses their outcomes in light of their potential to overcome the democratic malaise currently ailing Canada’s political system.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score0.999

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 studies0.0000.000
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 head0.083
GPT teacher head0.373
Teacher spread0.290 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations3
Published2007
Admission routes2
Has abstractyes

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