Co-Occurrence of Online and Offline Victimization: A Latent Class Analysis in University Students

Most people are exposed to risks both in the online and offline world. Several studies have provided definitions and measures of cybervictimization based on different theoretical approaches and most of them have focused on specific forms of cybercrime, depicting a limited portrayal of victimization. The current study explored victimization configurations in a sample of 749 university undergraduates from Spain (61.6% women; M age = 26.9), utilizing latent class analyses to account for the nature and frequency of various types of online and offline victimization along their life span. Among them, 35.9% were victims of a cyberattack, 24.4% reported being victims of cyberfraud and 49% of property crime. The analysis uncovered two classes of cybervictims—consisting of economic cybervictimization (victims of economic cybercrimes only) and cyber-polyvictimization (victims of various types of cybercrimes)—and allowed us to compare them with a group of non-victims. Younger respondents (15 to 25 years old), conventional university students, women, people with lower incomes and LGBTQI+ individuals have a higher representation in the cyber-polyvictimization class. In addition, members of this class have suffered more offline victimization in all the areas analyzed. The present study has found co-occurrence between online and offline victimization, thus reinforcing the relevance of simultaneously studying both areas and the interaction between them. From this empirical ground, prevention strategies should not be focused merely on opportunity factors related to the online interactions and behavior of potential victims, without facing the deep human and social roots of victimization.

Why US Democracy Trumps Populism: Comparative Lessons Reconsidered

ABSTRACT Matias López and Juan Luna (2021) challenged my comparative analysis of populism’s threat to democracy, its reliance on institutional factors (coupled with conjunctural opportunities), and especially the inference about US democracy’s immunity to populist suffocation. However, their emphasis on structuralist and culturalist factors, which would suggest the vulnerability of the United States, is strikingly selective, theoretically unconvincing, and empirically problematic. López and Luna’s methodological improvement of my analysis does not alter the substantive findings or overturn my sanguine inference about US democracy’s likely resilience. Only their further modifications yield more pessimistic scenarios, but those adjustments stand on shaky theoretical and empirical ground. Indeed, the experiences of 2020–2021 corroborate my theory and its comparative lessons. The US institutional framework held firm and foiled the insistent attempts of President Trump and his most fervent followers to perpetuate the US populist in power. Consequently, US democracy continues to appear quite safe from populist strangulation.

Constituency and left-sharing in coordination

A long-standing assumption in the syntactic literature is that coordination can only target constituents. This assumption has been a subject of much debate, with many authors questioning its validity. This article enters this debate by reconsidering a constraint on left-sharing in coordination which Osborne & Gross (2017) have recently introduced, namely left node blocking. To account for this constraint, Osborne & Gross propose the Principle of Full Clusivity which states that coordination cannot cut into a constituent. They couch their analysis in a Dependency Grammar, assuming that coordination does not have to conjoin constituents and that syntactic structures should be construed as flat. Given that the empirical ground on which the LNB is based is not firm, I seek to experimentally investigate it by conducting a large-scale experiment. The results of the investigation reveal that LNB is wrong; left-sharing is as permissive as right-sharing. The results of the investigation have the immediate consequence that the assumptions on which LNB is based are wrong as well, namely that syntactic structures should be construed as flat. I spell out an analysis couched in terms of left-to-right syntax to account for major cases of left-sharing in coordination.

A Primer for using INLA to Estimate Ground-Motion Models

This document provides a brief introduction int the use of the R package R-INLA for the development of empirical ground-motion models.

The Older The Better? The Strange Case of Empirical Ground Motion Models in the Near-Source of Moderate-To-Large Magnitude Earthquakes

This paper aims at providing a quantitative evaluation of the performance of a set of empirical ground motion models (GMMs), by testing them in a magnitude and distance range (Mw = 5.5 ÷ 7.0 and Joyner-Boore source-to-site distance Rjb ≤ 20 km) which dominates hazard in the highest seismicity areas of Italy for the return periods of upmost interest for seismic design. To this end, we made use of the very recent release of the NESS2.0 dataset (Sgobba et al., 2021), that collects worldwide near-source strong motion records with detailed metadata. After selection of an ample set of GMMs, based on either their application in past seismic hazard assessment (SHA) studies or for their recent introduction, a quantification of between- and within-event residuals of predictions with respect to records was performed, with the final aim of shedding light on the performance of existing GMMs in the near-source of moderate-to-large earthquakes, in view of a proper selection and weighting of GMMs for SHA.