Combating the ‘myth of physical restraint’ in human trafficking and modern slavery trials heard in the Crown Court

The greatest hurdle to an effective criminal justice response to human trafficking is the prevalence of myths about how exploitation happens and who ‘counts’ as a genuine victim. This includes the myth that, to be a genuine victim, an individual must have been subject to some form of physical restraint. Previous work has demonstrated how this myth undermines trafficking prosecutions in various jurisdictions. It has demonstrated that, in the absence of physical restraint during their exploitation, victims are deemed to lack credibility. However, what is missing in the current body literature is a robust analysis of whether something should be done to address this issue. By engaging with the foundational principle of accurate fact-finding, this article argues that some form of regulation of cross-examination in the English and Welsh jurisdiction, with a view to preventing this myth from manifesting in trials, would be justified.

The epistemic value of independent lies: false analogies and equivocations

Here I critically assess an argument put forward by Kuorikoski et al. (Br J Philos Sci, 61(3):541–567, 2010) for the epistemic import of model-based robustness analysis. I show that this argument is not sound since the sort of probabilistic independence on which it relies is unfeasible. By revising the notion of probabilistic independence imposed on the models’ results, I introduce a prima-facie more plausible argument. However, despite this prima-facie plausibility, I show that even this new argument is unsound in most if not all cases of model-based robustness analysis. This I do to demonstrate that the epistemic import of model-based robust analysis cannot be satisfactorily defended on the basis of probabilistic independence.

Mathematical Models to Measure the Variability of Nodes and Networks in Team Sports

Pattern analysis is a widely researched topic in team sports performance analysis, using information theory as a conceptual framework. Bayesian methods are also used in this research field, but the association between these two is being developed. The aim of this paper is to present new mathematical concepts that are based on information and probability theory and can be applied to network analysis in Team Sports. These results are based on the transition matrices of the Markov chain, associated with the adjacency matrices of a network with n nodes and allowing for a more robust analysis of the variability of interactions in team sports. The proposed models refer to individual and collective rates and indexes of total variability between players and teams as well as the overall passing capacity of a network, all of which are demonstrated in the UEFA 2020/2021 Champions League Final.

Nature Contact in the Carceral Workplace: Greenspace and Staff Sickness Absence in Prisons in England and Wales

This paper demonstrates for the first time that prisons with a higher proportion of natural vegetation within their perimeter have lower levels of staff sickness absence. It makes three significant contributions. First, it extends studies of workplace nature contact into the un-researched carceral context. Second, whereas previous workplace nature contact studies have largely utilized single-site surveys, it presents national-level, statistically robust analysis. Third, it brings a novel new perspective to studies of sickness absence within correctional workforces, by considering the effect of the physical environment. Econometric estimations presented in the paper confirm lower levels of staff sick-leave in prisons with more greenspace. This relationship persists when we control for prison size, security level, age, level of crowding, levels of self-harm and violence among prisoners, and assaults against staff. The findings are significant in demonstrating the benefits of nature contact in workplaces in general, and carceral environments in particular. Importantly, this has the potential to influence future prison design.