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Discourses of violence: an analysis of the construction of power and impact in university sexual harassment policies
Full text linkSexual harassment prevention within universities is a critical issue that is influenced through the framing of institutional policies. This study employs a feminist discourse analysis to examine the construction of sexual harassment in the policies of 30 English universities. The analysis focuses on how these policies describe power dynamics and the impact of harassment. The findings reveal a dominant discourse in line with the Equality Act (Gov.uk, 2010) that frames sexual harassment as harassment against a protected characteristic, with limited attention to the role of power or the image of the perpetrator. Alternative discourses present sexual harassment as either gender-based violence, focusing on power and perpetration, or as workplace aggression akin to bullying. Additionally, the study highlights that policies primarily emphasise the negative effects on individuals’ psychological and work-related wellbeing, often overlooking the adverse impacts of reporting harassment on both individuals and the broader community within a sexually hostile environment. Implications for policy are discussed
Decoding how higher-order network interactions shape complex contagion dynamics
Full text linkComplex contagion models that involve contagion along higher-order structures, such as
simplicial complexes and hypergraphs, yield new classes of mean-field models. Interestingly,
the differential equations arising from many such models often exhibit a similar form, resulting
in qualitatively comparable global bifurcation patterns. Motivated by this observation, we
investigate a generalized mean-field-type model that provides a unified framework for analysing
a range of different models. In particular, we derive analytical conditions for the emergence of
different bifurcation regimes exhibited by three models of increasing complexity—ranging from
three- and four-body interactions to two connected populations with both pairwise and three-
body interactions. For the first two cases, we give a complete characterisation of all possible
outcomes, along with the corresponding conditions on network and epidemic parameters. In the
third case, we demonstrate that multistability is possible despite only three-body interactions.
Our results reveal that single population models with three-body interactions can only exhibit
simple transcritical transitions or bistability, whereas with four-body interactions multistability
with two distinct endemic steady states is possible. Surprisingly, the two-population model
exhibits multistability via symmetry breaking despite three-body interactions only. Our work
sheds light on the relationship between equation structure and model behaviour and makes the
first step towards elucidating mechanisms by which different system behaviours arise, and how
network and dynamic properties facilitate or hinder outcomes
Reconfiguring Digital Accountability: AI-Powered Innovations and Transnational Governance in a Postnational Accounting Context
Full text linkThis study explores how AI-powered digital innovations are reshaping organisational accountability in a transnational governance context. As AI systems increasingly mediate decision-making in domains such as auditing and financial reporting, traditional mechanisms of accountability, based on control, transparency, and auditability, are being destabilised. We integrate the Technology Acceptance Model (TAM), Actor-Network Theory (ANT), and institutional theory to examine how organisations adopt AI technologies in response to regulatory, ethical, and cultural pressures that transcend national boundaries. We argue that accountability is co-constructed within global socio-technical networks, shaped not only by user perceptions but also by governance logics and normative expectations. Extending TAM, we incorporate compliance and legitimacy as key factors in perceived usefulness and usability. Drawing on ANT, we reconceptualise accountability as a relational and emergent property of networked assemblages. We propose two organisational strategies including internal governance reconfiguration and external actor-network engagement to foster responsible, legitimate, and globally accepted AI adoption in the accounting domain
Advances in the Synthesis of Carbon Nanomaterials Towards Their Application in Biomedical Engineering and Medicine
Full text linkCarbon nanomaterials that include different forms such as graphene, carbon nanotubes, fullerenes, graphite, nanodiamonds, carbon nanocones, amorphous carbon, as well as porous carbon, are quite distinguished by their unique structural, electrical, and mechanical properties. This plays a major role in making them pivotal in various medical applications. The synthesis methods used for such nanomaterials, including techniques such as chemical vapor deposition (CVD), arc discharge, laser ablation, and plasma-enhanced chemical vapor deposition (PECVD), are able to offer very precise control over material purity, particle size, and scalability, enabling for nanomaterials catered for different specific applications. These materials have been explored in a range of different systems, which include drug-delivery systems, biosensors, tissue engineering, as well as advanced imaging techniques such as MRI and fluorescence imaging. Recent advancements, including green synthesis strategies and novel innovative approaches like ultrasonic cavitation, have improved both the precision as well as the scalability of carbon nanomaterial production. Despite challenges like biocompatibility and environmental concerns, these nanomaterials hold immense promise in revolutionizing personalized medicine, diagnostics, and regenerative therapies. Many of these applications are currently positioned at Technology Readiness Levels (TRLs) 3–4, with some systems advancing toward preclinical validation, highlighting their emerging translational potential in clinical settings. This review is specific in evaluating synthesis techniques of different carbon nanomaterials and establishing their modified properties for use in biomedicine. It focuses on how these techniques establish biocompatibility, scalability, and performance for use in medicines such as drug delivery, imaging, and tissue engineering. The implications of nanostructure behavior in biological environments are further discussed, with emphasis on applications in imaging, drug delivery, and biosensing
Banning NDAs in Universities: A First Step Toward a Better Culture in the Economic Profession
Full text linkUnveiling the drivers of active participation in social media discourse
Full text linkThe emergence of new public forums in the form of online social media has introduced unprecedented challenges to public discourse, including polarization, misinformation, and the rise of echo chambers. Existing research has extensively examined these topics by focusing on the active actions performed by users, without accounting for the share of individuals who consume content without actively interacting with it. In contrast, this study incorporates passive consumption data to investigate the prevalence of active participation in online discourse. We introduce a metric to quantify the share of active engagement and analyze over 17 million pieces of content linked to a polarized Twitter debate to understand its relationship with several features of online environments, such as echo chambers, coordinated behavior, political bias, and source reliability. Our findings reveal a significant proportion of users who consume content without active interactions, underscoring the importance of considering also passive consumption proxies in the analysis of online debates. Furthermore, we found that increased active participation is primarily correlated with the presence of multimedia content and unreliable news sources, rather than with the ideological stance of the content producer, suggesting that active engagement is independent of echo chambers. Our work highlights the significance of passive consumption proxies for quantifying active engagement, which influences platform feed algorithms and, consequently, the development of online discussions. Moreover, it highlights the factors that may encourage active participation, which can be utilized to design more effective communication campaigns
Schizophrenia more employable than depression? Language-based artificial intelligence model ratings for employability of psychiatric diagnoses and somatic and healthy controls
Full text linkArtificial Intelligence (AI) assists recruiting and job searching. Such systems can be biased against certain characteristics. This results in potential misrepresentations and consequent inequalities related to people with mental health disorders. Hence occupational and mental health bias in existing Natural Language Processing (NLP) models used in recruiting and job hunting must be assessed. We examined occupational bias against mental health disorders in NLP models through relationships between occupations, employability, and psychiatric diagnoses. We investigated Word2Vec and GloVe embedding algorithms through analogy questions and graphical representation of cosine similarities. Word2Vec embeddings exhibit minor bias against mental health disorders when asked analogies regarding employability attributes and no evidence of bias when asked analogies regarding high earning jobs. GloVe embeddings view common mental health disorders such as depression less healthy and less employable than severe mental health disorders and most physical health conditions. Overall, physical, and psychiatric disorders are seen as similarly healthy and employable. Both algorithms appear to be safe for use in downstream task without major repercussions. Further research is needed to confirm this. This project was funded by the London Interdisciplinary Social Science Doctoral Training Programme (LISS-DTP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
Spring, Streets, and Chimney Sweeps: May Day in Regency London and Benjamin Robert Haydon’s Punch (1829)
Full text linkMay Day in Regency London was a festival for the climbing boy, the chimney sweep’s apprentice. An icon of poverty in Romantic Britain, the climbing boy stirred sympathy across the nation. However, on May Day, in London, this compassion was troubled by concerns for public safety and social order. Analyzing essays, illustrations, and ephemera, this article reframes the climbing boy, arguing that his raucous festivities often alienated him from the sympathy he typically evoked. It then examines how Benjamin Robert Haydon engaged with this pitiable yet disreputable figure in his major metropolitan genre painting Punch, or May Day
Byron’s Manfred (1817) and Tragedy in the ‘Mental Theatre’
No full textThis journal article presents a new interpretation of Byron’s work by setting out Byron’s approach to tragedy. Byron was a prolific tragedian, completing six tragic plays, but he insisted that his plays were closet dramas, to be experienced in the reader’s ‘Mental Theatre’, and not to be performed. While Byron’s attitude has often been dismissed by critics, this article takes his insistence on the reading of his plays as the starting point for understanding what Byron believed tragic drama should achieve and what it is for. Reading Byron’s preference for reading in the context of contemporary theatrical practices, the article contends that Byron’s preference for tragedy-as-read is rooted in his belief in the power of the imagination, and presents a vision of tragedy as something individual and private. It then provides a new reading of Byron’s play Manfred (1817) which both exemplifies and complicates this idea, and develops his vision of tragedy further. The article therefore offers a fresh way of approaching the genre of closet plays and the work of a key Romantic writer, and provides a new approach to tragedy which contributes to broader critical discussions about how tragedy is experienced and theorised