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Inovačné aktivity a ich význam v miestnej samospráve

2020· article· en· W3037601418 on OpenAlexaboutno aff
Michal Cifranič, Maroš Valach

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicHungarian Social, Economic and Educational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessInterviewGovernment (linguistics)Context (archaeology)Competition (biology)Order (exchange)Modernization theoryProcess (computing)Knowledge managementQuarter (Canadian coin)Local governmentPublic relationsProcess managementMarketingComputer sciencePolitical scienceFinanceEconomic growthPublic administrationEconomicsGeography

Abstract

fetched live from OpenAlex

Innovations are also an integral part of local self-government. If the self-government wants to keep up with growing claims of the citizens, or with very quick modernization of competition, it has to outlay the necessary effort to modernize itself and its offered services. The aim of the paper is to identify and analyse the innovative activities of the city of Košice and its quarter Košice - Staré Mesto with a focus on evaluating the innovation environment, identifying implemented innovations, evaluating the financing of innovations as well as the institutional context of their creation. Both primary and secondary data were used to identify and evaluate innovation activities. In order to obtain empirical data was used the interviewing method supported by the structured interview. The municipality perceives the need for innovations in order to increase the efficiency of ongoing processes within its organizational structures, which will enable citizens to provide better services. It also considers it necessary to increase the share of funding to support introducing innovations. So far, most resources have been focused on process and organizational innovations, many of which have been created by the Office's employees, which can be considered as original.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.116
GPT teacher head0.342
Teacher spread0.226 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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