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RETHINKING E‐GOVERNMENT PERFORMANCE ASSESSMENT FROM A CITIZEN PERSPECTIVE

2013· article· en· W2128493221 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePublic Administration · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsConsolidation (business)Information and Communications TechnologyPerspective (graphical)PoliticsPerceptionPublic relationsThe InternetE-GovernmentGovernment (linguistics)Order (exchange)Work (physics)BusinessKnowledge managementPolitical scienceEngineeringComputer sciencePsychology

Abstract

fetched live from OpenAlex

The use of information and communication technology ( ICT ), particularly that related to the consolidation of the internet as a social and business networking medium, has impelled governments towards enabling e‐government (e‐gov) programs to transform the future of the delivery of public services. E‐gov has a clear economic, social, and political impact that should be monitored in order to steer the design of effective public policies. In this article, we argue that evaluating the impact of e‐gov entails a complex process of e‐gov performance assessment that should take into account the perspective of citizens. Supported by a framework that combines two theoretical views, namely the structurationist view of technology and the social shaping of technology, we propose a model that consolidates nine performance dimensions. This model is the result of empirical work based on an in‐depth analysis of interviews with relevant social groups regarding their perceptions of the technological artefacts of e‐gov.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.995

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 studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.308
Teacher spread0.275 · 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