Revolutionising Marketing Education – A Sociocultural Approach to Praxis Pedagogy

This paper examines how the changing marketing landscape necessitates transformative learning approaches capable of preparing students for responsible and collaborative practice of marketing. It considers the potential of a Freirean praxis approach to marketing education informed by sociocultural theory to propose a framework for transformative learning.This is a conceptual piece integrating insights from Freire’s pedagogy and Vygotsky’s theory to propose a praxis pedagogies-based sociocultural framework for marketing education and ultimately employability.The paper identifies a set of key technological, environmental and societal factors impacting marketing and marketing education. In response to these, an integrative framework is provided to prepare students for the current and future challenges arising. Given the nature of the factors identified, this framework proposes a pedagogical approach that is not only critical but also socio-culturally informed.It adds to the burgeoning literature on responsible marketing education offering a theoretical and practical framework.This framework provides marketing educators with practical tools. Grounded in praxis and sociocultural theory, it equips students with critical thinking and collaboration skills, preparing them as marketers in response to societal and technological challenges.This approach is built on theory and exemplars directed at positive social change.The novelty of this pedagogical approach derives from the unique integration of theoretical perspectives from praxis and sociocultural theories towards transforming marketing education and thus practice in directions that are sustainable, socio-culturally grounded, and participatory

Meta-analysis finds large variation but no general patterns in the relationship between climate and parasitism in terrestrial animals

Climate can vary spatially and temporally and is becoming increasingly unpredictable due to climate change. It can have a large impact on host–parasite interactions and investigating this effect is vital both for understanding current parasite distribution and epidemiology, and predicting how this will change in the future. Here, we conducted a meta-analysis to determine whether temperature and precipitation have an overall effect on parasite prevalence and infection intensity in terrestrial animals. This is a phylogenetically controlled quantitative synthesis to assess parasite prevalence and infection intensity in terrestrial animals across contrasting temperatures and precipitation. We found large variation in the effect of temperature on parasite prevalence, precipitation on parasite prevalence, and temperature on infection intensity. This provides robust quantitative evidence against the controversial “warmer sicker world” hypothesis. There was no effect of climate on parasitism, irrespective of whether the parasite was an endoparasite or ectoparasite, or across different parasite lifecycles. Although some host and parasite taxa were understudied, we found no consistent taxonomic patterns. Importantly, we revealed large gaps in the literature, including the relationship between humidity, prevalence, and infection intensity. Ectoparasites and reptile hosts were also very underrepresented, and deserve further study. Focusing future research on these gaps will help to confirm whether certain types of host–parasite interactions are more or less sensitive to changes in climate, with implications for conservation

A Comparative Analysis of Machine Learning Based Power Flow Study with Custom Made Open Source Python Codes

Power flow analysis is a cornerstone of power system planning and operation, involving the solution of nonlinear equations to determine the steady-state operating conditions of the power grid. Traditionally, these equations are solved using iterative methods, which, despite their accuracy, are computationally intensive, may not converge to the solution and involve high time and space complexity. The challenges above can be overcome using Machine Learning (ML). Consequently, in this paper, a comprehensive comparative analysis of different ML algorithms developed for solving the power flow equations are presented. Experimental simulations for IEEE 3-bus and IEEE 118-bus networks have been conducted using custom-developed, open-source Python codes and technical insights are highlighted

Probing neutron star interiors and the properties of cold ultra-dense matter with the SKAO

Matter inside neutron stars is compressed to densities several times greater than nuclear saturation density, while maintaining low temperatures and large asymmetries between neutrons and protons. Neutron stars, therefore, provide a unique laboratory for testing physics in environments that cannot be recreated on Earth. To uncover the highly uncertain nature of cold, ultra-dense matter, discovering and monitoring pulsars is essential, and the SKA will play a crucial role in this endeavour. In this paper, we will present the current state-of-the-art in dense matter physics and dense matter superfluidity, and discuss recent advances in measuring global neutron star properties (masses, moments of inertia, and maximum rotation frequencies) as well as non-global observables (pulsar glitches and free precession). We will specifically highlight how radio observations of isolated neutron stars and those in binaries -- such as those performed with the SKA in the near future -- inform our understanding of ultra-dense physics and address in detail how SKAO's telescopes unprecedented sensitivity, large-scale survey and sub-arraying capabilities will enable novel dense matter constraints. We will also address the potential impact of dark matter and modified gravity models on these constraints and emphasise the role of synergies between the SKA and other facilities, specifically X-ray telescopes and next-generation gravitational wave observatories

Gender Dynamics in Political Leadership: The Impact of Female Party Leaders on Ideological Perceptions

This thesis investigates the impact of female party leadership on the perceived ideological positioning of political parties, addressing two key research questions: first, how the gender of a party leader influences voters’ perceptions of the party’s ideological stance; and second, how voters’ perceptions and expert assessments respond to leadership changes involving a transition from male to female leaders. Using original datasets documenting party leaders’ gender identities and leadership transitions across multiple countries, the study reveals significant findings. For left-wing parties, the presence of a female leader does not significantly affect the perceived ideological stance of the party. However, for right-wing parties, a female leader is associated with a notable shift in public perception of the party’s ideology further to the right–contrary to stereotypes portraying women as more progressive. Additionally, the thesis uncovers an unexpected rightward shift in expert assessments following transitions from male to female leadership in right-wing parties. This counterintuitive finding diverges from existing literature and suggests complexities in how gendered leadership changes influence expert positions. Voter assessments, by contrast, appear largely unaffected by such transitions. These findings illuminate the multifaceted ways in which gender dynamics shape public and expert perceptions of political parties, challenging traditional assumptions and contributing to a deeper understanding of the interplay between gender, leadership, and political ideology. This research offers valuable insights for scholars in political science and gender studies alike. <br/

Contested Illnesses: An Exploration of Experience and Understanding

Contested Illnesses (CIs) are illnesses without determinable aetiology. Despite diverse symptomologies, CIs share limited therapeutic avenues, indeterminate diagnostic protocols, and contestation over the legitimacy of the illness. This thesis explores the lived experiences of virtual symbolic community (VSC) members with myalgic encephalomyelitis (ME), fibromyalgia (FM) and morgellons disease (MD), focusing on how VSC use impacts CI patients. This research is the first sociological investigation of MD from the patient perspective and expands existing scholarship on ME and FM. It examines the applicability of epistemic injustice – a concept that addresses the inequality among possessors and wielders of knowledge – to the CI patient experience, uncertainty, and previously undiscussed forms of knowledge production. Utilising online ethnographic and semi-structured interviews, this research provides an in-depth analysis of the lived experiences of individuals with ME, FM, and MD, the influence of VSC community cultures on CI patients, and the benefits and drawbacks of VSC participation. The analysis highlights the significance of experiences of uncertainty within medical, social, psychological, future, and moral domains. Applying epistemic injustice to the CI context reveals the impact of testimonial and hermeneutical injustices, which obscure personal understanding and limit positive health outcomes. VSCs play a crucial role in creating and exchanging knowledge and unlearning processes, providing members with valuable resources for navigating their illness journey. Finally, this research underscores the importance of VSCs in supporting CI patients, highlights the drawbacks of VSC participation, and contributes to the broader discourse on patient experiences and online health communities. The collective findings illuminate the application of a final theoretical insight, to what extent ME, FM, and MD are medicalised on the three interlinked levels, and what this insight may tell us about CIs more broadly. <br/