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Record W2891054079 · doi:10.31618/vadnd.v1i13.138

EXPERIENCE OF ADVANCED COUNTRIES IN APPLICATION OF PRE-TRIAL SETTLEMENT IN CONSTRUCTION

2018· article· en· W2891054079 on OpenAlexaff
Олександра Марушева

Bibliographic record

VenueUKRAINIAN ASSEMBLY OF DOCTORS OF SCIENCES IN PUBLIC ADMINISTRATION · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLand Use and Management
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsUkrainianSettlement (finance)Context (archaeology)LegislationState (computer science)Political scienceOrder (exchange)DecentralizationPoliticsPublic administrationLaw and economicsLawBusinessSociologyComputer scienceFinanceGeography

Abstract

fetched live from OpenAlex

The paper highlights the practice of pre-trial settlements in the sphere of construction in advanced countries of the world. Specific features of scientific theoretical approaches to dispute settlement in construction works have been substantiated. The international experience of advanced countries in application of the mechanisms for alternative dispute resolution has been analyzed, and a comprehensive research into international legal acts has been conducted. The vector of priority directions and ways to introduce the alternative mechanisms in the conditions of the Ukrainian state are determined. It is proposed to achieve the desired results by applying the discussed forms under administrative system reform. It is noted that today the Ukrainian state is only at the stage of creating an alternative dispute resolution model in construction. It is noted that the idea of introducing this practice in the domestic legal system is supported by a wide range of specialists. Such an interest corresponds to the desire of Ukraine to harmonize national legislation. It is grounded that the definition of priority directions and ways of introducing alternative mechanisms in the field of construction in Ukraine is to apply foreign experience in the context of reforming the modern political system, namely decentralization. It is the application of the proposed model that should be implemented at the state, regional and local levels, legally consolidate it and solve urgent problems. Such a systematization, in my opinion, will lead to a more objective and perfect settlement of disputes over a short period of time. It is noted that nowadays there is a considerable scientific interest in this issue, the expediency of using alternative mechanisms in the Ukrainian state is solved. However, this is a rather controversial issue, so there is a need for a comprehensive study of experience in foreign countries and the identification of priority areas and ways of applying experience in modern conditions in Ukraine.

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)0.013
metaresearch head score (Gemma)0.010
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0070.008
Scholarly communication0.0050.004
Open science0.0010.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.025
GPT teacher head0.362
Teacher spread0.337 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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