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E-Participation and Canadian Parliamentarians

2007· book-chapter· en· W2506544546 on OpenAlexaffabout
Mary Francoli

Bibliographic record

VenueIGI Global eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsCarleton University
Fundersnot available
KeywordsDemocracyPolitical scienceGovernment (linguistics)PoliticsCitizenshipPrime ministerPublic administrationInformation and Communications TechnologyThe InternetPublic relationsLaw

Abstract

fetched live from OpenAlex

During the last decade, the public policies of many countries have emphasized the need for greater citizen participation in decision-making, and governments have been adopting e-government strategies as a means of not only improving service delivery, but also engaging society and revitalizing democracy. Indeed, many political leaders have been advancing the democratic potential of information and communication technologies (ICTs). British Prime Minister Tony Blair, for example, has stated: “I believe that the information society can revitalize our democracy...innovative electronic media is pioneering new ways of involving people of all ages and backgrounds in citizenship through new Internet and digital technology ... that can only strengthen democracy” (Hansard Society, 2004). Similarly, former United States President Bill Clinton stated that ICTs would “give the American people the Information Age that they deserve—to cut red tape, improve the responsiveness of government toward citizens, and expand opportunities for democratic participation” (Prins, 2001, p. 79). In Canada, former Prime Minister Paul Martin also argued, along the same vein, that people need to be brought into the decision-making process if the country is to have the kind of future that it needs, indicating that ICTs are a useful means of achieving this goal (Speech to the 2003 Crossing Boundaries Conference, Ottawa Canada).

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.812
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.036
GPT teacher head0.304
Teacher spread0.268 · 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

Citations6
Published2007
Admission routes2
Has abstractyes

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