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Record W2113130772 · doi:10.1007/0-306-47374-7_17

E-Government in Canada

2002· book· en· W2113130772 on OpenAlexaffabout
Jeffrey Roy

Bibliographic record

Venue˜The œKluwer international series on advances in database systems · 2002
Typebook
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsUniversity of OttawaInstitute on Governance
Fundersnot available
KeywordsGovernment (linguistics)Digital governmentContext (archaeology)Foundation (evidence)Public administrationKey (lock)E-GovernmentPublic relationsPolitical scienceSection (typography)BusinessDigital transformationInformation and Communications TechnologyComputer scienceGeographyAdvertisingComputer security

Abstract

fetched live from OpenAlex

The objectives of this chapter are first, to examine the main conceptual dimensions of electronic government and second, to critically assess Canada’s public sector. The following definition of e-government is a starting point: the continuous innovation in the delivery of services, citizen participation, and governance through the transformation of external and internal relationships by the use of information technology, especially the Internet. For some, e-governance is distinguishable from e government in that the former comprises a more fundamental sharing and reorganizing of power across all stakeholders and the citizenry, whereas the latter is more focused on modernizing existing state processes to improve performance with respect to existing services and policies. In the short term, digital technologies continue to serve primarily as a platform for incremental changes to the service and security architectures. Yet, broader pressures and questions about transparency and trust continue to build. A key question is whether or not a new government is prepared to embrace a more holistic redesign of political institutions predicated on information openness and public engagement.Request access from your librarian to read this chapter's full text.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.547
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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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 designNot applicable
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

Citations12
Published2002
Admission routes2
Has abstractyes

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Same venue˜The œKluwer international series on advances in database systemsSame topicE-Government and Public ServicesFrench-language works237,207