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Record W1540400086 · doi:10.1504/ijpp.2010.035133

Developing fundamental capabilities for successful e-government implementation

2010· article· en· W1540400086 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

VenueInternational Journal of Public Policy · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsCarleton UniversityMcMaster University
Fundersnot available
KeywordsInformation and Communications TechnologyDeveloping countryGovernment (linguistics)E-GovernmentBusinessProcess managementKnowledge managementComputer scienceEconomic growthEconomicsWorld Wide Web

Abstract

fetched live from OpenAlex

Several researchers address the failure of e-government (EG) in developing countries. Researchers studying the failure of information and communication technology (ICT) and EG systems reveal that the initiative, strategy, and adoption criteria of ICT in developing countries do not follow the same track as in developed countries. The failure to manage ICT and adopt EG systems arises from two points – the government itself and the citizens. The objective of this study is to identify the determinants and critical factors that contribute to government development of fundamental capabilities to adopt and manage ICT and successfully implement EG systems. This research study, applying qualitative methodology in a developing country, identifies the fundamental capabilities required to implement EG in developing countries, and the critical factors required to develop the capabilities necessary to adopt ICT and implement EG.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
Research integrity0.0000.000
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 head0.043
GPT teacher head0.408
Teacher spread0.365 · 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