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Record W4396760878 · doi:10.15802/rtem2023/292671

INTERNATIONAL COMPETITIVENESS OF UKRAINE IN THE FIELD OF RAIL TRANSPORT

2024· article· en· W4396760878 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueREVIEW OF TRANSPORT ECONOMICS AND MANAGEMENT · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Systems and Logistics Management
Canadian institutionsnot available
Fundersnot available
KeywordsField (mathematics)BusinessEconomic geographyRegional scienceGeographyMathematics

Abstract

fetched live from OpenAlex

The purpose of this article is to determine the competitive position of Ukraine in the field of railway transportation in comparison with Poland (a neighbouring country), Switzerland (a benchmark in the field of railway transportation) and Canada (which professes a completely different “American” principle of operating railway networks, where freight transportation is a priority). Methods. In the process of working on the article, the following research methods were used: analysis and synthesis in the selection of indicators and their grouping (production and financial, scientific and technical development, personnel characteristics) depending on the direction they characterise; methods of economic analysis – multidimensional comparative analysis, index analysis, Delphi method in determining the weight of indicators selected for analysis, rating to determine the final positions of each of the countries selected for analysis. Results. Among the main results of the study is the determination of Ukraine’s competitive position, primarily in comparison with Poland as a neighbouring country. The next most important is the group of indicators that put Ukraine behind the Swiss railways’ benchmarks, in particular, the quality of infrastructure and electrification. The scientific novelty of the results obtained is an attempt to assess the competitive positions of railway transport, which seemingly cannot compete with each other, since each of them operates in a separate territory (in most cases within the same country) and their interests hardly overlap. Currently, this is not entirely true, since, after the large-scale invasion, due to the blockade of Ukrainian seaports, a significant part of export and import commodity flows has moved to rail transport, and by analysing the situation in each individual transit country, it is possible to choose the direction that will be most acceptable for the long-distance transportation of goods to “third” countries. The practical significance of the results obtained can be viewed from at least two perspectives. The first is the indicators that have caused the Ukrainian railway to lag behind the benchmark state (Switzerland) and the work to improve the situation in each of the areas. The second side is the possibility of conducting a similar assessment of the situation in rail transport among all of Ukraine’s neighbouring countries and identifying the highest priority areas for sending most of the export and import cargo to “third” countries.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.021
GPT teacher head0.247
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