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Record W2114551370 · doi:10.1108/tg-01-2014-0001

Interactions with e-government, new digital media and traditional channel choices: citizen-initiated factors

2014· article· en· W2114551370 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTransforming Government People Process and Policy · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Channel (broadcasting)OriginalityService (business)Value (mathematics)Digital mediaSurvey data collectionPublic relationsBusinessComputer sciencePolitical scienceMarketingTelecommunicationsWorld Wide WebStatisticsMathematics

Abstract

fetched live from OpenAlex

Purpose – This paper aims to examine the factors that can predict citizen-initiated contact with e-government as an attempt to identify important differences between service channel selections. Although more than two decades have passed since the initiation of e-government, digital channel choice is still being questioned, compared to traditional channels, and the level of selection with channels is being investigated. Design/methodology/approach – This study states three research questions that are answered through a literature review and statistical analysis of a survey in a developed country. More specifically, it identifies the factors that impact channel choice and validates them with survey results. To this end, this paper utilizes data from a national Canadian survey, where citizens empirically evaluated their channel choice – e-government, new digital media and traditional service channels – for government contacts. Findings – Statistical analysis over this data return valuable findings such as that the e-government channel is more appropriate for information collection, whereas traditional service channels are more likely to establish individual problem solving. Moreover, the digital divide appears to have an impact on citizen channel choice. Furthermore, digitally literate citizens who are aware of privacy issues are more likely to use new digital media. Finally, citizens are quite satisfied from their new digital media experience, but are not as satisfied with their traditional contact experience. Originality/value – These outcomes show that e-government obstacles regarding digital divide, trust and efficiency remain active and have to be addressed more carefully by governments. This study shows that e-government and new digital media are not simple channel choices, but are complex in public service delivery. These outcomes confirm the significance of channel choice for transforming government, as e-government appears to be a part of a broader channel choice agenda.

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.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score0.908

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 studies0.0010.000
Scholarly communication0.0000.002
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 head0.032
GPT teacher head0.278
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