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Record W4392424006 · doi:10.6000/1929-4409.2020.09.368

Monitoring and Evaluation of the Implementation Process of the State Policy to Promote the Development of Civil Society in Ukraine

2021· article· en· W4392424006 on OpenAlexvenueno aff
Liudmyla Prykhodchenko, Andrii Krupnyk, Alla I. Orlova, Oksana V. Dulina

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)Process (computing)Civil societyPolitical sciencePublic administrationProcess managementLawBusinessComputer sciencePolitics

Abstract

fetched live from OpenAlex

Among the components of the cycle of state policy to promote the development of civil society in Ukraine, the process of its implementation is studied. In particular, the current state of monitoring and evaluation (ME) of this process was analysed, scientific developments on this topic were reviewed and the authors' own approach to the implementation of state policy in this area was proposed. The ME of the process of implementation of the National Strategy for Civil Society Development for 2016-2020 in Ukraine (hereinafter – the National Strategy) as the main legal act that ensures the implementation of state policy in this area at national, regional and local levels of public administration, was studied. The basic requirements to the organisation of the ME of the process of implementation of the National Strategy in terms of periodicity, multilevel, organisational and methodological support, forms of control were formulated. A set of evaluation criteria and indicators was proposed and recommendations for the organisation of this process were provided. The provided recommendations can be the basis for the creation and implementation of the ME system for the implementation of the National Strategy. The results of the ME process of implementation of the current National Strategy can be used in the development of a new National Strategy for the next period after 2020.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.137

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.102
GPT teacher head0.384
Teacher spread0.282 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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