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Record W1593497077

Successful Community Municipal Portal Diffusion: Internal Government Factors and Individual Perceptions

2009· article· en· W1593497077 on OpenAlexaffabout
Brian Detlor, Maureen Hupfer, Li Zhao, Umar Ruhi

Bibliographic record

VenueJournal of the Association for Information Systems · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGovernment (linguistics)PerceptionDemographicsBusinessLocal governmentQuality (philosophy)E-GovernmentKnowledge managementPublic relationsPsychologyComputer sciencePolitical scienceWorld Wide WebPublic administrationSociologyInformation and Communications Technology
DOInot available

Abstract

fetched live from OpenAlex

This paper presents findings and research directions of an in-progress study examining the factors affecting successful community municipal portal diffusion. Several community municipal portal sites in the Province of Ontario, Canada are being investigated via questionnaires sent to portal administrators at six portal sites, and web surveys completed by 1,753 end-users at five of these six sites. In the study’s first round, internal government factors shaping the implementation of community municipal portals, as well as usage patterns and end-user demographics, are identified. The study’s second and third rounds use these results to test a new theoretical framework that comprises both internal government factors and individual perceptions. Importantly, information quality is suggested to be a key individual perceptions factor that not only affects successful community municipal portal diffusion, but also plays a pivotal role in mediating the effect of internal government factors on a person’s use of a community municipal portal site.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
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 head0.024
GPT teacher head0.282
Teacher spread0.258 · 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 designObservational
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

Citations0
Published2009
Admission routes2
Has abstractyes

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