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Record W3091797487 · doi:10.21272/mmi.2020.3-21

The Law Aspects in Health Management: A Bibliometric Analysis of Issues on the Injury, Damage and Harm in Criminal Law

2020· article· en· W3091797487 on OpenAlexaboutno aff
Zamina Aliyeva

Bibliographic record

VenueMarketing and Management of Innovations · 2020
Typearticle
Languageen
FieldMedicine
TopicLegal, Health, Environmental and COVID-19 Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsHarmScopusCriminal lawPolitical scienceMistakeDrug controlLawBusinessCriminologyPsychologyMEDLINE

Abstract

fetched live from OpenAlex

The paper presents the analysis of the approaches to define the areas of research on the injury, damage and harm to human health in criminal law. The obtained results proved that crimes, connected to drugs abuse, their legislation become an essential part of the issues. At the same, developing of government control, medical standards, improving quality of medical education balancing the «medical mistake – injury to human’s health – jurisprudence consequences» triangle in the tendency of the injury, damage and harm in criminal laware becoming very important to the healthcare system due to increasing requirements of regulators, customers and shareholders. The paper aimed to analyse the tendency in the literature on the injury, damage and harm in criminal law, which published in books, journals, conference proceedings etc. to identify future research directions. The methodological tools are VOSviewer, Scopus and Web of Science (WoS) software. This study covers 1072 papers from Scopus and WoS database. The time for analysis were 1970-2020. The Scopus and WoS analyse showed that in 2012-2019 the numbers of papers on the injury, damage and harm in criminal law issues began to increase. However, the topics changed from general issues to the problem of decriminalisation of drug trafficking, and the corresponding paradigm shift in the punishment of some crimes, increasing interest in punishing corporations for violating environmental regulations. In 2017 the number of documents dedicated to injury, damage and harm in criminal law was increased by 667% compared to 2012. The main subject areas of analyses of the injury, damage and harm in criminal law were the next: Law, Public environmental, occupational health, Criminology penology, Substance abuse, Psychiatry, Medicine. The biggest amount of investigations of the injury, damage and harm in criminal law was published by the scientists from the USA, United Kingdom, Australia and Canada. In 2019 such journals with high impact factor as International Journal of Drug Policy, International Journal of Law and Psychiatry, The Lancet etc. published the number of issues, which analysed of the injury, damage and harm to human health in criminal law. Such results proved that theme on the injury, damage and harm to human health in criminal law is actually in the ongoing trends of the modern jurisprudence and regulation. The findings from VOSviewer defined 6 clusters of the papers which analysed the injury, damage and harm to human health in criminal law from the different points of views. The first biggest cluster (with the biggest number of connections) merged the keywords as follows: criminal justice, law enforcement, public health, health care policy, harm reduction, drug legislation, drug and narcotic control, substance abuse, homelessness etc. The second significant cluster integrated the keywords as follows: criminal behaviour, crime victim, adolescent, violence, mental health, mental disease, prisoner, young people, rape, police etc. The third biggest cluster concentrated on criminal aspects of jurisprudence, criminal law, human right, legal liability, social control, government regulation etc. The obtained results allow concluding that balancing the triangles «medical mistakes – criminal – education» and «drugs – criminal – justice» and «abortion – criminal – women/children» form an important part of the injury, damage and harm in criminal law issues. Keywords injury, damage, harm, human health, criminal law, management, governance.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.022
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 head0.045
GPT teacher head0.331
Teacher spread0.286 · 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

Labeled directly by 2 models reading the full record.

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

Citations7
Published2020
Admission routes1
Has abstractyes

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Same venueMarketing and Management of InnovationsSame topicLegal, Health, Environmental and COVID-19 ChallengesCategoryBibliometricsFrench-language works237,207