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Record W2810981524 · doi:10.29379/jedem.v7i2.406

International Challenges to Transformational Government: Enhanced Project Management Identifies Need for Existential Change

2015· article· en· W2810981524 on OpenAlexaff
Shauneen Furlong

Bibliographic record

VenueJeDEM - eJournal of eDemocracy and Open Government · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTransformational leadershipMindsetExistentialismGovernment (linguistics)Change management (ITSM)BusinessProcess managementPolitical sciencePublic relationsKnowledge managementComputer scienceMarketing

Abstract

fetched live from OpenAlex

The case for transformational eGovernment continues unabated; impatient stakeholders are more demanding; people, process and content are profoundly impacted; opportunity is rampart - but so is risk and complexity; still, transformational eGovernment remains more theoretical than practical. Execution has faltered and relief is not obvious.Enhanced project management has made progress in advancing eGovernment by applying enhanced project management in a holistic manner so that project activities are fully integrated with on-going operational activities: all with an emphasis on measurable results and outcomes.This paper, however, concludes that there is another dimension to the transformational eGovernment navigation tool-kit that coalesces with enhanced project management and creates a multi-dimensional approach to transformation; it is existential change leadership that focuses on human mindset behaviour.Thus, the next step in the research is to examine a two-pronged approach (enhanced project management and existential change leadership) to respond to the challenges and barriers that have long impeded transformational eGovernment progress and the accountability vacuum for the elusive transformational breakthrough results

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
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 head0.262
GPT teacher head0.415
Teacher spread0.153 · 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 designNot applicable
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

Citations3
Published2015
Admission routes1
Has abstractyes

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