In this paper we study persistence features of topological entropy and periodic orbit growth of Hamiltonian diffeomorphisms on surfaces with respect to Hofer's metric. We exhibit stability of these dynamical quantities in a rather strong sense for a specific family of maps studied by Polterovich and Shelukhin. A crucial ingredient comes from enhancement of lower bounds for the topological entropy and orbit growth forced by a periodic point, formulated in terms of the geometric self-intersection number and a variant of Turaev's cobracket of the free homotopy class that it induces. Those bounds are obtained within the framework of Le Calvez and Tal's forcing theory.

“According to [Bayesian] models” in cognitive neuroscience, says a recent textbook, “the human mind behaves like a capable data scientist”. Do they? That is: do such models show we are rational? I argue that Bayesian models of cognition, perhaps surprisingly, don’t and indeed can’t, show that we are Bayesian-rational. The key reason is that they appeal to approximations, a fact that carries significant implications. After outlining the argument, I critique two responses, seen in recent cognitive neuroscience. One says that the mind can be seen as approximately Bayes-rational, while the other reconceives norms of rationality.

Uchiyama et al. emphasize that culture evolves directionally and differentially as a function of selective pressures in different populations. Extending these principles to the level of families, lineages, and individuals exposes additional challenges to estimating heritability. Cultural traits expressed differentially as a function of the genetics whose influence they mask or unmask render inseparable the influences of culture and genetics.

Boundaries are defined and maintained to establish and preserve cultural, societal and political integrity. Boundaries change as territorial structures and their related meanings change over time, reflecting the transformation of economic, political, administrative and cultural practices and discourses, and inherent relations of power. The Israeli metropolis of Tel Aviv is no different in this context. The end of World War I and establishment of a British Mandate regime in Palestine resulted in the transformation of political, economic, social and cultural structures. The British Mandate afforded the rise of and development of Tel Aviv from Jaffa's Jewish garden suburb into a separate urban entity. Different internal and external factors affected the delineation of the urban bounds of Tel Aviv following its declaration by the British Mandate government as an autonomous township.

Scholars contend that the reason for stasis in human rights measures is a biased measurement process, rather than stagnating human rights practices. We argue that bias may be introduced as part of the compilation of the human rights reports that serve as the foundation of human rights measures. An additional source of potential bias may be human coders, who translate human rights reports into human rights scores. We first test for biases via a machine-learning approach using natural language processing and find substantial evidence of bias in human rights scores. We then present findings of an experiment on the coders of human rights reports to assess whether potential changes in the coding procedures or interpretation of coding rules affect scores over time. We find no evidence of coder bias and conclude that human rights measures have changed over time and that bias is introduced as part of monitoring and reporting.

This editorial expands on a Praxis article published by Beattie and colleagues in the trainees’ section of this journal. The authors describe an interesting case of anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis, outline the clinical presentation and make suggestions on ways to approach this rare disorder. Here we provide an overview of autoimmune conditions that result in the production of autoantibodies targeting central nervous system proteins mediating autoimmune encephalitis and offer a perspective on approaches to diagnosis and treatment.

The study of language acquisition has a long and contentious history: researchers disagree on what drives this process, the relevant data, and the interesting questions. Here, I outline the Starting Big approach to language learning, which emphasizes the role of multiword units in language, and of coarse-to-fine processes in learning. I outline core predictions and supporting evidence. In short, the approach argues that multiword units are integral building blocks in language; that such units can facilitate mastery of semantically opaque relations between words; and that adults rely on them less than children, which can explain (some of) their difficulty in learning a second language. The Starting Big approach is a theory of how children learn language, how language is represented, and how to explain differences between first and second language learning. I discuss the learning and processing models at the heart of the approach and their cross-linguistic implications.

This article gives a general overview of the current situation in relation to a range of widely recognised and also newly identified types of child maltreatment. The academic and clinical evidence relating to the impact of child maltreatment on the mental and physical health of child victims is substantial and steadily increasing in volume. New types of abuse are being identified, and changing environmental circumstances, which exacerbate the possibility of widely recognised types of child maltreatment occurring, are also being described. These include multi-type maltreatment, female genital mutilation and online child maltreatment. Serious questions may arise regarding neglect of the moral and social development of children and young people who become addicted to online gaming and pornography. Multiple national and local definitions of each of these existing and new forms of maltreatment have been created, some of which are covered here. The impact of these abuses on the physical and mental health and development of child victims in families or settings where abuse or neglect has occurred is discussed.

Human trafficking affects millions of people globally, disproportionately harming women, girls and marginalized groups. Yet one of the main sources of data on global trafficking, the annual Trafficking in Persons (TIP) Reports, is susceptible to biases because report rankings are tied to political outcomes. The literature on human rights measurements has established two potential sources of bias. The first is the changing standards of accountability, where more information and increased budgets change the standard to which countries are held over time. The second is political biases in reports, which are amended to comply with the interests of the reporting agency. This letter examines whether either of these biases influence the TIP Reports. In contrast to other country-level human rights indicators, the State Department issues both narratives and rankings, which incentivizes attempts to influence the rankings based on political interests. The study uses a supervised machine-learning algorithm to examine how narratives are translated into rankings, to determine whether rankings are biased, and to disentangle whether bias stems from changing standards or political interests. The authors find that the TIP Report rankings are more influenced by political biases than changing standards.

An understanding of the current state of mental health services in the United Arab Emirates (UAE) from a clinical perspective is an important step in advising government and stakeholders on addressing the mental health needs of the fast-growing population. We conducted a retrospective study of data on all patients admitted to a regional psychiatric in-patient unit between June 2012 and May 2015. More Emiratis (UAE nationals) were admitted compared with expatriates. Emiratis were diagnosed more frequently with substance use disorders and expatriates with stress-related conditions. Psychotic and bipolar disorders were the most common causes for admission and had the longest in-patient stays; advancing age was associated with longer duration of in-patient stay.

A number of philosophers draw a close analogy between scientific modeling and fiction, often appealing to Kendall Walton’s make-believe view. I assess the models-fictions analogy from a cognitive angle, suggesting that from this perspective it appears relatively weak. More specifically, I argue that, on the one hand, the appeal to Walton is appropriate inasmuch as his view fits well with how modelers employ the imagination. On the other hand, what makes Walton’s view attractive as an account of the cognitive aspects of modeling makes it less attractive as an account of fiction.

Multiword units play an important role in language learning and use. It was proposed that learning from such units can facilitate mastery of certain grammatical relations, and that children and adults differ in their use of multiword units during learning, contributing to their varying language-learning trajectories. Accordingly, adults learn gender agreement better when encouraged to learn from multiword units. Previous work has not examined two core predictions of this proposal: (1) that children also benefit from initial exposure to multiword units, and (2) that their learning patterns reflect a greater reliance on multiword units compared to adults. We test both predictions using an artificial-language. As predicted, both children and adults benefit from early exposure to multiword units. In addition, when exposed to unsegmented input – adults show better learning of nouns compared to article-noun pairings, but children do not, a pattern consistent with adults’ predicted tendency to focus less on multiword units.