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Although the prevalence of cybercrime has increased rapidly, most victims do not report these offenses to the police. This is the first study that compares associations between victim characteristics and crime reporting behavior for traditional crimes versus cybercrimes. Data from four waves of a Dutch cross-sectional population survey are used (N = 97,186 victims). Results show that cybercrimes are among the least reported types of crime. Moreover, the determinants of crime reporting differ between traditional crimes and cybercrimes, between different types of cybercrime (that is, identity theft, consumer fraud, hacking), and between reporting cybercrimes to the police and to other organizations. Implications for future research and practice are discussed. doi: https://doi.org/10.1177/1477370818773610 This article is honored with the European Society of Criminology (ESC) Award for the “Best Article of the Year 2019”. Dit artikel is bekroond met de European Society of Criminology (ESC) Award for the “Best Article of the Year 2019”.
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Reporting of research findings is often selective. This threatens the validity of the published body of knowledge if the decision to report depends on the nature of the results. The evidence derived from studies on causes and mechanisms underlying selective reporting may help to avoid or reduce reporting bias. Such research should be guided by a theoretical framework of possible causal pathways that lead to reporting bias. We build upon a classification of determinants of selective reporting that we recently developed in a systematic review of the topic. The resulting theoretical framework features four clusters of causes. There are two clusters of necessary causes: (A) motivations (e.g. a preference for particular findings) and (B) means (e.g. a flexible study design). These two combined represent a sufficient cause for reporting bias to occur. The framework also features two clusters of component causes: (C) conflicts and balancing of interests referring to the individual or the team, and (D) pressures from science and society. The component causes may modify the effect of the necessary causes or may lead to reporting bias mediated through the necessary causes. Our theoretical framework is meant to inspire further research and to create awareness among researchers and end-users of research about reporting bias and its causes.
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This study systematically evaluates greenhouse gas (GHG) emissions reporting practices of European airline groups, covering both mandatory and voluntary key performance indicators (KPIs) under evolving regulatory frameworks. By analysing annual and sustainability reports from 16 major airline groups, the research identifies significant progress in the reporting of core metrics, with Scope 1 CO2 totals reported by 94 % and emissions intensity by 88 %, reflecting growing regulatory alignment and stakeholder expectations. However, persistent gaps remain: Scope 2 and Scope 3 reporting appears in only 56 % and 50 % of cases, respectively, while non-CO2 emissions are disclosed by just 38 %, despite forthcoming European Union Emissions Trading System (EU ETS) monitoring requirements. Reporting on sustainable aviation fuels (SAF) life-cycle emissions is limited (19 %), and CO2 offsetting disclosures are rare (6 %), complicating verification of decarbonisation claims and readiness for ReFuelEU Aviation and Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA). The proliferation of voluntary KPI disclosures further complicates comparability due to a lack of standardization and clear definitions. These challenges are compounded by risks of greenwashing, where airlines selectively report favourable data such as emissions intensity, and greenhushing, where substantive achievements are under-communicated. The study concludes that while regulatory frameworks such as the Corporate Sustainability Reporting Directive (CSRD), the EU ETS, CORSIA, and ReFuelEU are driving improvements, further harmonization and methodological clarity are required to ensure transparency, comparability, and genuine progress toward aviation's climate goals.
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Abstract-Architecture Compliance Checking (ACC) is useful to bridge the gap between architecture and implementation. ACC is an approach to verify conformance of implemented program code to high-level models of architectural design. Static ACC focuses on the modular software architecture and on the existence of rule violating dependencies between modules. Accurate tool support is essential for effective and efficient ACC. This paper presents a study on the accuracy of ACC tools regarding dependency analysis and violation reporting. Seven tools were tested and compared by means of a custom-made test application. In addition, the code of open source system Freemind was used to compare the tools on the number and precision of reported violation and dependency messages. On the average, 74 percent of 34 dependency types in our custom-made test software were reported, while 69 percent of 109 violating dependencies within a module of Freemind were reported. The test results show large differences between the tools, but all tools could improve the accuracy of the reported dependencies and violations.
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The Junior Adverse Drug Event Manager (J-ADEM) team is a multifaceted intervention focusing on real-life education for medical students that has been shown to assist healthcare professionals in managing and reporting suspected adverse drug reactions (ADRs) to the Netherlands Pharmacovigilance Centre Lareb. The aim of this study was to quantify and describe the ADRs reported by the J-ADEM team and to determine the clinical potential of this approach. The J-ADEM team consisted of medical students tasked with managing and reporting ADRs in hospitalized patients. All ADRs screened and reported by J-ADEM team were recorded anonymously, and categorized and analysed descriptively. From August 2018 through January 2020, 209 patients on two wards in an academic hospital were screened for ADR events. The J-ADEM team reported 101 ADRs. Although most ADRs (67%) were first identified by healthcare professionals and then reported by the J-ADEM team, the team also reported an additional 33 not previously identified serious ADRs. In 10% of all reported ADRs, the J-ADEM team helped optimize ADR treatment. The ADR reports were largely well-documented (78%), and ADRs were classified as type A (66%), had a moderate or severe severity (85%) and were predominantly avoidable reactions (69%). This study shows that medical students are able to screen patients for ADRs, can identify previously undetected ADRs and can help optimize ADR management. They significantly increased (by 300%) the number of ADR reports submitted, showing that the J-ADEM team can make a valuable clinical contribution to hospital care.
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The Standard for Public Code gives public organizations a model for preparing open source solutions to enable collaborations with similar public organizations in other places. It includes guidance for policy makers, city administrators, developers and vendors.
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There appears to be some hesitation within the forensic biology community to formally evaluate and report on findings given activity level propositions. This hesitance in part stems from concerns about the lack of relevant data on the dynamics of biological traces and doubt about the relevance of such expert opinions to the trier of fact. At the Netherlands Forensic Institute formal evaluative opinions on the probability of case findings given propositions at the activity level are provided since 2013, if requested by a mandating authority. In this study we share the results from a retrospective analysis of 74 of such requests. We explore which party initiates requests, the types of cases that are submitted, the sources of data being used to assign probabilities to DNA transfer, persistence, prevalence and recovery (TPPR) events, the conclusions that were drawn by the scientists, and how the conclusions were used by the courts. This retrospective analysis of cases demonstrates that published sources of data are generally available and can be used to address DNA TPPR events in most cases, although significant gaps still remain. The study furthermore shows that reporting on forensic biology findings given activity level propositions has been generally accepted by the district and appeal courts, as well as the other parties in the criminal justice system in the Netherlands.
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Calls have been made for improving transparency in conducting and reporting research, improving work climates, and preventing detrimental research practices. To assess attitudes and practices regarding these topics, we sent a survey to authors, reviewers, and editors. We received 3,659 (4.9%) responses out of 74,749 delivered emails. We found no significant differences between authors’, reviewers’, and editors’ attitudes towards transparency in conducting and reporting research, or towards their perceptions of work climates. Undeserved authorship was perceived by all groups as the most prevalent detrimental research practice, while fabrication, falsification, plagiarism, and not citing prior relevant research, were seen as more prevalent by editors than authors or reviewers. Overall, 20% of respondents admitted sacrificing the quality of their publications for quantity, and 14% reported that funders interfered in their study design or reporting. While survey respondents came from 126 different countries, due to the survey’s overall low response rate our results might not necessarily be generalizable. Nevertheless, results indicate that greater involvement of all stakeholders is needed to align actual practices with current recommendations.
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SUMMARY Architecture compliance checking (ACC) is an approach to verify conformance of implemented program code to high-level models of architec tural design. Static ACC focuses on the modular software architecture and on the existence of rule violating dependencies between modules. Accurate tool support is essential for effective and efficient ACC. This paper presents a study on the accuracy of ACC tools regarding dependency analysis and violation reporting. Ten tools were tested and compare d by means of a custom-made benchmark. The Java code of the benchmark testware contains 34 different types of dependencies, which are based on an inventory of dependency types in object oriented program code. In a second test, the code of open source system FreeMind was used to compare the 10 tools on the number of reported rule violating dependencies and the exactness of the dependency and violation messages. On the average, 77% of the dependencies in our custom-made test software were reported, while 72% of the dependencies within a module of FreeMind were reported. The results show that all tools in the test could improve the accuracy of the reported dependencies and violations, though large differences between the 10 tools were observed. We have identified10 hard-to-detect types of dependencies and four challenges in dependency detection. The relevance of our findings is substantiated by means of a frequency analysis of the hard-to-detect types of dependencies in five open source systems. DOI: 10.1002/spe.2421
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This method paper presents a template solution for text mining of scientific literature using the R tm package. Literature to be analyzed can be collected manually or automatically using the code provided with this paper. Once the literature is collected, the three steps for conducting text mining can be performed as outlined below:
• loading and cleaning of text from articles,
• processing, statistical analysis, and clustering, and
• presentation of results using generalized and tailor-made visualizations.
The text mining steps can be applied to a single, multiple, or time series groups of documents.
References are provided to three published peer reviewed articles that use the presented text mining methodology. The main advantages of our method are: (1) Its suitability for both research and educational purposes, (2) Compliance with the Findable Accessible Interoperable and Reproducible (FAIR) principles, and (3) code and example data are made available on GitHub under the open-source Apache V2 license.
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