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Record W4283756814 · doi:10.37335/ijek.v10i1.140

DEVELOPMENT OF INITIATED BANKRUPTCIES IN SLOVAKIA AND THE CZECH REPUBLIC

2022· article· en· W4283756814 on OpenAlexaboutno aff
Martin Bič

Bibliographic record

VenueInternational Journal of Entrepreneurial Knowledge · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicImpact of AI and Big Data on Business and Society
Canadian institutionsnot available
FundersVedecká Grantová Agentúra MŠVVaŠ SR a SAV
KeywordsCzechBankruptcyQuarter (Canadian coin)InsolvencyBusinessCoronavirus disease 2019 (COVID-19)AccountingGeographyFinanceDiseaseMedicine

Abstract

fetched live from OpenAlex

Nowadays, entrepreneurs can very easily find themselves in a bad financial situation. That is why it is essential to look for ways to help them effectively. However, this cannot be done without knowing the real situation in each country, which is the basis for creating the appropriate conditions. The study's main objective was to identify and compare the development of insolvency indicators representing the bankruptcy of entrepreneurs in Slovakia and the Czech Republic from the first quarter of 2017 to the second quarter of 2021. Descriptive analysis and primary research methods were used to achieve this objective. The analytical processing dealt with the indicator of initiated bankruptcies. A fluctuating decline was observed in both countries. In 2020, a slight increase was recorded, and a further increase can be expected due to the coronavirus disease 2019 (COVID-19) pandemic. 2018 and 2017 were the least positive years for Slovakia and the Czech Republic, respectively. The results indicated the need for interventions in the business environment of both countries to help entrepreneurs in bad situations.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.147
GPT teacher head0.401
Teacher spread0.254 · 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 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

Citations5
Published2022
Admission routes1
Has abstractyes

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