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Record W3171298450 · doi:10.6000/1929-4409.2021.10.73

Protection of the Right to Information on One’s Health – A Non-Jurisdictional Form of Protection

2021· article· en· W3171298450 on OpenAlexvenueno aff
Nataliia Khodieieva, Mykola Yasynok, Yurii Kuryliuk, Станіслав Філіппов, Alla Zemko, Dmytro Yasynok

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldMedicine
TopicLegal, Health, Environmental and COVID-19 Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsRight to healthAppealHealth protectionHealth informationData Protection Act 1998LawBusinessPolitical scienceComputer securityMedicineComputer scienceEnvironmental healthHuman rightsHealth care

Abstract

fetched live from OpenAlex

The article analyzes the theoretical aspects of protection as directly subjective civil rights and defines them within the framework of civil relations regarding the information on one's health. A clearer and complete description of the features of the realization of the right to information on one's health in the normatively established system of protection of subjective rights of a person has been obtained. It has been determined that the protection of the right to information on one's health is exercised freely, and the failure of a person to exercise the right to protection is not a ground for termination of this right. It is noted that during the protection of their violated right to health information, the authorized person may perform certain actions that are not related to the appeal to the competent state bodies and are a non-jurisdictional form of protection. The list of actions of an individual to protect the right to information on one’s health in the case of a non-jurisdictional form of protection of the above-mentioned right has been systematized.

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)0.020
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.024
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.058
Scholarly communication0.0090.007
Open science0.0020.009
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.047
GPT teacher head0.320
Teacher spread0.273 · 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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Criminology and SociologySame topicLegal, Health, Environmental and COVID-19 ChallengesFrench-language works237,207