Peer grading is an educational system in which students assess each other’s work. It is commonly applied under Massive Open Online Course (MOOC) and offline classroom settings. With this system, instructors receive a reduced grading workload, and students enhance their understanding of course materials by grading others’ work. Peer grading data have a complex dependence structure, for which all the peer grades may be dependent. This complex dependence structure is due to a network structure of peer grading, where each student can be viewed as a vertex of the network, and each peer grade serves as an edge connecting one student as a grader to another student as an examinee. This article introduces a latent variable model framework for analyzing peer grading data and develops a fully Bayesian procedure for its statistical inference. This framework has several advantages. First, when aggregating multiple peer grades, the average score and other simple summary statistics fail to account for grader effects and, thus, can be biased. The proposed approach produces more accurate model parameter estimates and, therefore, more accurate aggregated grades by modeling the heterogeneous grading behavior with latent variables. Second, the proposed method provides a way to assess each student’s performance as a grader, which may be used to identify a pool of reliable graders or generate feedback to help students improve their grading. Third, our model may further provide insights into the peer grading system by answering questions such as whether a student who performs better in coursework also tends to be a more reliable grader. Finally, thanks to the Bayesian approach, uncertainty quantification is straightforward when inferring the student-specific latent variables as well as the structural parameters of the model. The proposed method is applied to two real-world datasets.

Presidential primary elections arguably represent the most dynamic campaigns in American politics. Television advertising is a key aspect of strategy that candidates can marshal throughout the campaign. We develop a methodology for measuring the impact of advertising in primary elections that accounts for endogeneity and apply it to the 2000 through 2016 elections. We find that advertisements—both positive and negative—improve the favorability and the vote share of the candidate running the ads. We find that negative advertising is more effective than positive advertising, but that only high polling candidates lose support when attacked.

Previously, we reported the persistence of the bacterial pathogen Neisseria meningitidis on fomites, indicating a potential route for environmental transmission. The current goal was to identify proteins that vary among strains of meningococci that have differing environmental survival. We carried out a proteomic analysis of two strains that differ in their potential for survival outside the host. The Group B epidemic strain NZ98/254 and Group W carriage strain H34 were cultured either at 36 °C, 5% CO2, and 95% relative humidity (RH) corresponding to host conditions in the nasopharynx, or at lower humidities of 22% or 30% RH at 30 °C, for which there was greater survival on fomites. For NZ98/254, the shift to lower RH and temperature was associated with increased abundance of proteins involved in metabolism, stress responses, and outer membrane components, including pili and porins. In contrast, H34 responded to lower RH by decreasing the abundance of multiple proteins, indicating that the lower viability of H34 may be linked to decreased capacity to mount core protective responses. The results provide a snapshot of bacterial proteins and metabolism that may be related to normal fitness, to the greater environmental persistence of NZ98/254 compared to H34, and potentially to differences in transmission and pathogenicity.

This article studies the robustness of quasi-maximum-likelihood estimation in hidden Markov models when the regime-switching structure is misspecified. Specifically, we examine the case where the data-generating process features a hidden Markov regime sequence with covariate-dependent transition probabilities, but estimation proceeds under a simplified mixture model that assumes regimes are independent and identically distributed. We show that the parameters governing the conditional distribution of the observables can still be consistently estimated under this misspecification, provided certain regularity conditions hold. Our results highlight a practical benefit of using computationally simpler mixture models in settings where regime dependence is complex or difficult to model directly.

Mapping reviews are valuable tools for synthesizing and visualizing research evidence, providing a comprehensive overview of studies within a specific field. Their visual approach enhances accessibility, enabling researchers, policymakers, and practitioners to efficiently identify key findings, trends, and knowledge gaps. These reviews are particularly significant in guiding future research, informing funding decisions, and shaping evidence-based policymaking. In environmental science—similar to health and social sciences—mapping reviews play a crucial role in identifying effective conservation strategies, tracking interventions, and supporting targeted programs.

Unlike systematic reviews, which assess intervention effectiveness, mapping reviews focus on broad research questions, aiming to chart the existing evidence on a given topic. They use structured methodologies to identify patterns, gaps, and trends, often employing visual tools to enhance data accessibility. A well-defined scope, guided by inclusion and exclusion criteria, ensures a transparent study selection process. Comprehensive search strategies, often spanning multiple databases, maximize evidence capture. Effective screening, combining automated and manual processes, ensures relevance, while data extraction emphasizes high-level categories such as study design and population demographics. Advanced software tools, including EPPI-Reviewer and MindMeister, support data extraction and visualization, with evidence gap maps highlighting robust areas and research voids.

Despite their advantages, mapping reviews present challenges. The categorization and coding of studies can introduce subjective biases, and the process demands substantial resources. Automation and artificial intelligence offer promising solutions, improving efficiency while addressing integration and multilingual limitations. As methodological advancements continue, interdisciplinary collaboration will be essential to fully realize the potential of mapping reviews across scientific disciplines.

The Elizabethan reign has lately emerged as a formative period for English ideas about the liberties of the subject and the ‘ancient constitution’ of the realm. Recent work has described the development of such ideas as having been driven by an organized campaign against the English ecclesiastical courts: a legal and intellectual effort that had emerged from the misgivings of certain ‘puritan’ lawyers about the powers claimed by new prerogative jurisdictions. The primary grievance of the campaign has been identified as having been the church courts’ use of the oath ex officio, and the campaign’s primary defensive tool has been identified as having been the twenty-ninth chapter of Magna Carta. But overlooked manuscripts reveal a more complex story. This article shows that the law of excommunication was as important to the campaign in question as Magna Carta. In addition, a re-examination of the life and work of James Morice, one of the principal lawyers responsible for the campaign, demonstrates that the law of excommunication deeply structured his understanding of the royal supremacy, and of the legal relationship between England’s secular and ecclesiastical polities – particularly as they had existed in the distant medieval past.

Affective polarization is often blamed on the rise of partisan news. However, self-reported measures of news consumption suffer serious flaws. We often have limited ability to characterize partisan media audiences outside of the United States. I use a behavioural data set of 728 respondents whose online behaviour was tracked over four weeks during the 2019 Canadian federal election. These data were paired to a survey for a subset of respondents. I find that audiences for partisan media are small, and web traffic is driven by an even smaller share of the population. There are few major partisan differences in news media use, and partisan news exposure is higher among highly attentive, sophisticated news consumers, rather than those with strong political commitments.

We introduce the framework FreeCHR which formalizes the embedding of Constraint Handling Rules (CHR) into a host language, using the concept of initial algebra semantics from category theory. We hereby establish a high-level implementation scheme for CHR as well as a common formalization for both theory and practice. We propose a lifting of the syntax of CHR via an endofunctor in the category Set and a lifting of the very abstract operational semantics of CHR into FreeCHR, using the free algebra, generated by the endofunctor. We give proofs for soundness and completeness with its original definition. We also propose a first abstract execution algorithm and prove correctness with the operational semantics. Finally, we show the practicability of our approach by giving two possible implementations of this algorithm in Haskell and Python. Under consideration in Theory and Practice of Logic Programming.

Galen’s most deeply held professional values included clarity of expression and the epistemological importance of clinical experience. Therefore, it is not surprising that he thought and wrote about communication with patients. His stories about patients show that he questioned them about their symptoms and history, and some stories explicitly teach the lesson that this type of questioning is important. His stories often quote patients indirectly or directly; they are often told partly from the patient’s perspective, and some contain constructions indicating that Galen paid attention to an individual patient’s exact words. In On the Affected Parts, his discussion of the vocabulary of pain – a problem in medical communication still important today – he privileges the common usage of patients over the technical vocabulary invented by Archigenes. He argues that only by listening to patients and their words can we construct a useful vocabulary of metaphors for pain that can bridge the gap in experience between physician and patient. He does not dismiss the words of women or enslaved patients; on the other hand, in a few stories where the patriarch of a family is present and the patient is female or enslaved, Galen’s dialogue tends to engage the head of the household rather than the patient. While some of his stories show off his ability to diagnose patients without talking to them, and others raise the problem of the lying patient, none of these stories would have meaning unless the patients’ words were normally crucial to clinical practice.

There is a lack of knowledge on deaths related to police use of force across Canada. Tracking (In)Justice is a research project that is trying to make sense of the life and death outcomes of policing through developing a collaborative, interdisciplinary, and open-source database using publicly available sources. With a collaborative data governance approach, which includes communities most impacted and families of those killed by police, we document and analyze 745 cases of police-involved deaths when intentional force is used across Canada from 2000 to 2023. The data indicate a steady rise in deaths, in particular shooting deaths, as well as that Black and Indigenous people are over-represented. We conclude with reflections on the ethical complexities of datafication, knowledge development of what we call death data and the challenges of enumerating deaths, pitfalls of official sources, the data needs of communities, and the living nature of the Tracking (In)Justice project.

We present a fully three-dimensional kinetic framework for modeling intense short pulse lasers interacting with dielectric materials. Our work modifies the open-source particle-in-cell code EPOCH to include new models for photoionization and dielectric optical response. We use this framework to model the laser-induced damage of dielectric materials by few-cycle laser pulses. The framework is benchmarked against experimental results for bulk silica targets and then applied to model multi-layer dielectric mirrors with a sequence of simulations with varying laser fluence. This allows us to better understand the laser damage process by providing new insight into energy absorption, excited particle dynamics and nonthermal excited particle distributions. We compare common damage threshold metrics based on the energy density and excited electron density.

Since its inception in 2009, Argentina’s Universal Child Allowance (AUH) has become the country’s most comprehensive social protection policy for children, emphasising standardisation and objectivity. However, its implementation occurs in contexts of poverty and inequality, leading to uneven outcomes across communities. This study examines how street-level bureaucrats adapt large-scale policies like the AUH to local contexts marked by deep social disparities. Although the AUH is designed for standardized and automated implementation, frontline workers play a critical role in adjusting the policy to specific territorial needs. These bureaucrats employ informal strategies and policy improvisation to mitigate institutional weaknesses and address gaps in the AUH’s rigid framework. By analysing the interplay between the policy’s institutional design, frontline workers, and adaptations, this study sheds light on how street-level bureaucracies at multiple levels enable these workers to navigate local challenges and partially compensate for broader institutional fragility.

‘Tropicalization’, the phenomenon of species shifting their ranges, has become increasingly prevalent as a response to environmental modifications induced by global change. This study points to an accelerated tropicalization process of marine fish species in the Gulf of Cadiz, a bioinvasion hotspot adjacent to the Strait of Gibraltar. We report accelerated, unusual, and rare occurrences of 15 fish species expanding and potentially establishing their ranges in the Gulf of Cadiz, driven by ocean warming over the past decade. These new insights are the combined consequence of a range expansion of some species, likely facilitated by temperature increases, an intensification of maritime traffic (with a consequent rise in propagule pressure), and a possible increase in sampling efforts and citizen science.