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Record W3126922944 · doi:10.46925//rdluz.32.27

International experience on the improvement of national management technology and legal regulation of public contracts

2021· article· en· W3126922944 on OpenAlexaboutno aff
Viktoriia Holubieva, Лілія Михайлівна Невара, Serhiy Savchuk, Andriy Detiuk, Валерій Тацієнко

Bibliographic record

VenueRevista de la Universidad del Zulia · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Fiscal Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementNormativeChinaBusinessUnificationPublic administrationPolitical scienceLawMarketing

Abstract

fetched live from OpenAlex

The objective of the research is to study the global experience of the legal regulation and organization of public procurement (from a not only legal but also a technological perspective), which should be the basis for suggestions to improve the legal regulation mechanism for procurement public in Ukraine. For the implementation of the comparative legal part of the study, normative legal acts and acts of official interpretation of the legal systems of the following states, as well as related scientific and scientific-practical materials, were used: USA, Australia, New Zealand, Japan, Switzerland, South Korea, United Kingdom, Japan, Egypt, Canada, Malaysia, Israel, India, Argentina, Australia, New Zealand. The unification of electronic public procurements systems remains to be a topical and unresolved task for the WTO GPA member countries. The experience of some countries in encouraging small and medium-sized enterprises in electronic public procurement is considered progressive and positive. We consider it necessary to adopt the experience of the USA, Israel, China countries and accelerate the adoption of laws in Ukraine to support national producers.

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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.221
Teacher spread0.201 · 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 designTheoretical or conceptual
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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRevista de la Universidad del ZuliaSame topicEconomic and Fiscal StudiesFrench-language works237,207