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Record W3133899955 · doi:10.18757/jisss.2021.1.4638

Identifying common grounds for safety and security research: a comparative scientometric analysis focusing on development patterns, similarities, and differences

2020· article· en· W3133899955 on OpenAlexafffund
Jie Li, Floris Goerlandt, Karolien van Nunen, Genserik Reniers

Bibliographic record

VenueJournal of Integrated Security and Safety Science · 2020
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsScope (computer science)Engineering ethicsKnowledge managementComputer scienceEngineering

Abstract

fetched live from OpenAlex

Safety and security are often considered in complimentary or opposing terms. Discussions on their conceptual meaning have been put forward, and calls for an increased integration of these domains have been made. Nevertheless, there is currently no high-level empirical comparison of the development and contents of these research domains. In this article, the broad scientific literature of safety and security research obtained from Web of Science is analysed, aiming to obtain comparative insights in these respective fields, with a specific focus on the themes, topics and scientific areas where increased integration can be fruitful. Scientific publications are analysed in terms of research trends and geographic distribution, journals’ distribution, scientific categories, and focus topics of safety and security research in 2019. The results indicate a rapidly growing publication trend in both research domains, with an exponential growth since the 1990s. Safety research focuses on medicine/drug safety, patient safety and disease-related safety, with occupational health and safety and safety in socio-technical systems comparatively smaller research domains. Security research focuses on internet of things, physical layer security and cybersecurity/information security. Journals and scientific categories where significant contributions to both safety and security research are made relate mostly to industrial and transport safety and security, food safety, and public, environmental and occupational health. Apart from providing insights to academics and practitioners to the scope and focus areas of safety and security research, the findings also support delineating the scope and focus of the Journal of Integrated Security and Safety Science (JISSS), which aims to bolster connections and integration between these domains. Based on the findings, a focus on safety and security in industrial plants, transportation contexts, and industrially relevant aspects of public, environmental and occupational health, is found to be an appropriate target area for JISSS.

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)0.050
metaresearch head score (Gemma)0.198
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.198
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.1600.195
Science and technology studies0.0030.004
Scholarly communication0.0120.011
Open science0.0010.007
Research integrity0.0020.001
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 head0.342
GPT teacher head0.520
Teacher spread0.178 · 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.

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

Citations4
Published2020
Admission routes2
Has abstractyes

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