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Record W3116369032 · doi:10.3390/jrfm14010002

The Event of Croatia’s EU Accession and Membership from the Croatian High School Students’ Perspective

2020· article· en· W3116369032 on OpenAlexvenueno aff
Anamarija Pisarović, Sanja Tišma, Krševan Antun Dujmović, Mira Mileusnić Škrtić

Bibliographic record

VenueJournal of risk and financial management · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccessionEuropean unionPerceptionEvent (particle physics)Political scienceCroatianPopulationPublic opinionPublic relationsPsychologySociologyBusinessDemographyLawPoliticsInternational trade

Abstract

fetched live from OpenAlex

The knowledge, attitudes and perceptions of the high school students on Croatia’s European Union (EU) accession event were omitted in numerous public opinion polls conducted since the 2013 accession. Therefore, the paper shows key benefits of Croatia’s EU accession and the recent attitudes of high school students about the meaning of this event for their future lives. Research methods include desktop analysis regarding previous researches of the population attitudes and a quantitative survey conducted in January 2017 on a sample of a total of 1944 school graduates who were interviewed on issues of knowledge, perception and attitude to the event of Croatia’s entrance and membership in the EU. The results point out that although Croatia acquires significant benefits from the EU accession, the very event is not recognized as being the key one by high school students. Considering that in many cases the youth opinion is the best indicator of overall social problems and considering the future programs and obligations as well as the role expected from the youth in implementation of these programs, the research findings on the perception of the event of Croatia’s accession to the EU are a field within which future policy activities are envisaged.

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)0.001
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 score0.698
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.293
Teacher spread0.275 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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