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Record W2168475075 · doi:10.1177/0894439302238967

New Technologies and Institutional Change in Public Administration

2003· article· en· W2168475075 on OpenAlexaff
Mila Gascó‐Hernández

Bibliographic record

VenueSocial Science Computer Review · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsNew institutionalismIncentiveInterdependenceGovernment (linguistics)Civil societyPublic administrationCorporate governanceConstitutionInstitutional economicsMultidisciplinary approachBusinessInstitutional analysisAdministration (probate law)Public sectorInstitutional changePublic relationsPolitical scienceSociologyEconomicsPoliticsMarket economySocial science

Abstract

fetched live from OpenAlex

This article aims to study and analyze, from a multidisciplinary point of view, the organizational and institutional transformations that public administration is experiencing due to a country’s transition to the information and knowledge society. Three specific goals are pursued: (a) studying the use of new technologies in the public administration, (b) studying the impact brought about by the use of new technologies by the public administration, and (c) studying the institutional changes caused by the use of these technologies. To achieve these goals, three guiding lines are considered: first, the term governance; that is, the collection of institutions and rules that set the limits and the incentives needed for the constitution and functioning of interdependent networks of actors (government, private sector and civil society actors); second, the new institutionalism perspective; and finally, the relationship between technology and organizational and institutional change.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.012
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0050.033
Scholarly communication0.0120.011
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.093
GPT teacher head0.362
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations119
Published2003
Admission routes1
Has abstractyes

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