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Record W4300835627 · doi:10.5937/bezbednost2202044t

Free legal aid for victims of gender-based violence from the perspective of lawyers

2022· article· en· W4300835627 on OpenAlexaboutno aff
Вељко Турањанин, Jelena Čanović

Bibliographic record

VenueBezbednost Beograd · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Legal researchPerspective (graphical)Political scienceLawLegal practiceSubject (documents)Legal professionPsychologyCriminologySociologyGeographyComputer scienceLibrary science

Abstract

fetched live from OpenAlex

The paper deals with the right to free legal aid for victims of gender-based violence in the Republic of Serbia. The Law on Free Legal Aid entered into force in November 2019, and after two and a half years, there are certain shortcomings in the implementation visible in practice. The paper is divided into several parts, and the authors explain the background of the research in the introductory considerations, emphasizing the key legal provisions that were the subject of the research, after which the main part of the paper presents the results of the research conducted in the first quarter of 2022. The questionnaire sent to lawyers contained 22 questions, with a focus on providing free legal aid to victims of gender-based violence, for the period since November 1, 2019. The results show that the legal framework, but also the practice of providing free legal aid by local governments, is not at a satisfactory level.

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)0.004
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.293
Teacher spread0.269 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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