Arts and Social Sciences Journal

This paper examined the relationship between graffiti writing and the law in Nigeria, with specific focus on the regulatory regimes available to graffiti arts and artists. Qualitative research design and methods were used, with oral interview and documentary study preferred for empirical investigations. Four respondents were orally interviewed. Some online documents – legal materials, newspaper reports, and academic writings – were also studied. Findings revealed that graffiti were now accepted as legitimate arts in Nigeria. In regulating the disturbing aspects of graffiti, the same sets of rules used for the mainstream arts were being applied. The available rules were, however, considered as inadequate for the effective governance of the online documented graffiti to control abuses. But where the existing rules were properly enforced and obeyed, there would be the rightful recognition of the artists, the appreciation of their style of art, and improved income for the artists and the country at large, among other benefits. For a better regulation and graffiti writing in Nigeria, artists should collectively work to ensure timely and broad distributions of knowledge about the ethics of the practice for new entrants; there should be increased allocations of writing spaces for graffiti artists across the States to encourage the practice, promote the aesthetics of local communities, provide alternative therapeutic avenues for disenfranchised youths, and reduce the chances of malicious damage to public property. The Nigerian governments should also establish a visionary, credible and viable council to best manage the alternative art sector.

Art has long been a powerful medium for expressing and challenging societal norms. While traditional forms like painting and sculpture continue to play a crucial role, the emergence of performance art has brought a new dimension to artistic expression. Beyond the Canvas, Performance Art has become a dynamic and impactful way to engage audiences, provoke thought, and spark conversations about social issues. This article explores the roots of performance art, its evolution, and its profound impact on social awareness.

The transition to sustainable and resilient energy systems is one of the most pressing challenges of our time. As we strive to mitigate climate change and secure energy access for growing populations, energy system models have become essential tools for planning and policy-making. Traditionally, these models have focused on the technical and economic aspects of energy systems, often overlooking the equally crucial sociotechnical factors. This article aims to present the present situation of examining socio-technical factors in energy system models and suggest future directions for enhancing the integration of these vital aspects. Energy system models have typically emphasized the technical and economic dimensions, considering energy sources, technologies, costs, and emissions. While these are undoubtedly important, they represent only one side of the complex energy equation. Socio-technical factors encompass the social, cultural, political, and behavioral aspects that influence energy production, consumption, and management. Neglecting these factors can lead to models that are inadequate for understanding and guiding energy system transitions.

The relationship between social overhead capital facilities and housing prices has been a subject of interest and debate in the field of urban economics for several decades. Social overhead capital refers to essential public infrastructure and services that are fundamental for the wellbeing of a community. These include schools, hospitals, transportation networks, parks, and more. It is widely believed that the presence and quality of such facilities can significantly impact housing prices in a given area. In this article, we delve into this intricate relationship between social overhead capital facilities and housing prices, employing a machine learning approach to analyse data and draw insights. Machine learning has emerged as a powerful tool in urban economics, enabling researchers to uncover patterns and correlations in vast datasets that were previously challenging to process manually. By leveraging this technology, we can gain a deeper understanding of how social overhead capital influences housing prices and its implications for urban development and policy.