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The purpose of this paper is to study the popular educational broadcasting of Julius Sumner Miller and its intersections with contemporary science policy and education.

The paper draws on archival research including resources so far unused by historians of science or of broadcasting and audio-visual resources of Sumner Miller’s broadcasts on Australian, Canadian and American television. It begins by contextualising Sumner Miller as both an academic and broadcaster. The second section interprets the core points of his educational philosophy which he articulated in his written and broadcast works. The final section uses his private papers contextualised by works on the history and philosophy of science to interpret and delineate the disparity between Sumner Miller’s influence as a populariser of science and the prevailing trends in scientific policy and teaching.

This paper proposes that reconstructing the themes and recurring points he asserted in his broadcasts reveals disjunction between Sumner Miller’s high-profile successes and the contemporary trends in both science policy and science education. This paper interprets the circumstance of an internationally known and influential science populariser who was coterminous with but against the grain of the notion of “big science”. He therefore sought to popularise science precisely as it was developing in ways he disparaged.

This paper breaks new ground by interpreting the different sources, audio-visual and written, created by and about an influential television broadcaster.

Although he was widely and internationally known, and the range of his influence on science communication is generally noted, Sumner Miller’s broadcasting and the themes and educational philosophy espoused in it is little researched and contextualised. This paper sharpens understanding of his influence but also his points of intersection and disjunction with scientific culture. Hitherto unused archival resources contribute to this understanding.

Inequality in the creative industries often serves as the starting point for public debates over culture in the UK. Academic literature has long recognised the precarious nature of the fashion industry. This chapter offers a critical review of the relationships of power existing in the support offered to ethnic minorities in disadvantaged communities in the fashion and creative sectors in the UK. In addressing these issues, a Foucauldian perspective is adopted. The chapter focuses on Black, Asian, and minority ethnic (BAME) fashion entrepreneurs’ challenges in promoting young designers from disadvantaged communities.

Our findings show that the BAME entrepreneurs are active agents who are essential in identifying and shaping new creative and talented young designers. The chapter contributes to the debate through a critical review of the relationships of power existing in the support offered to ethnic minorities in disadvantaged communities in the fashion and creative sectors in the UK.

There are often relational interactions in teams that lead to and drive the spread of work engagement. Despite the potential social impacts on work engagement, such as coworker support and organizational citizenship behaviors within teams, they have rarely been studied from a social perspective using social network analysis (SNA). This review draws on the crossover model and conservation of resources theory to suggest that the effects of social diffusion and the exchange of resources can impact Well-Being, specifically work engagement, in teams and that SNA can help measure those social interactions. Linking several network concepts – closeness centrality, density, degree centrality, and tie strength – to work engagement propositions related to the spread of work engagement as well as the number and quality of network ties, this review elucidates the potential for integrating SNA methodology to the field of Well-Being for teams.

The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.

We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.

Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.

These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.

Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.