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The Prevent policy was singular and ‘simple’: to prevent individuals from getting drawn into terrorism, to identify and stop this process before it begins. In the context of the global war on terror and the shadow of terrorist attacks in the United States and England, this was an increasingly growing issue within the media and the broader public discourse. A central institution charged with enacting Prevent in the United Kingdom were education institutions (schools, colleges and universities), the rationale being that these places of learning house individuals during impressionable and vulnerable times and the Prevent policy can protect these individuals.

This chapter will provide an alternative critical discussion on Prevent by framing it as the securitisation of the UK education sector. As such, Prevent is a form of surveillance and a mechanism of power over educators and learners which carry counterproductive consequences for both. In doing so, this chapter will question how education professionals balance their professional identity and their new role in supporting and enacting the Prevent duty. Through developing a new multi-level ‘Critical Realist World Systems Model’, this chapter will provide a conceptual discussion of Prevent policy more broadly and how education professionals navigate the friction between their professional values and legal obligations. This chapter draws on a range of theoretical traditions to begin to question a well-established security policy within English and Welsh educational institutions providing a conceptual starting point to examine similar and future policies.

The Metaverse is rapidly reshaping the understanding of tourism, yet the public perception of this new domain remains largely uncharted empirically. This paper aims to build on the technology acceptance model (TAM) and diffusion of innovations theory (DIT) to fill this gap, offering crucial insights that could inform scholars and practitioners in both the tourism and technology sectors.

Using a big-data approach, the authors applied machine learning to scrape comments made by social media users on recent popular posts or videos related to tourism in the Metaverse from three prominent social media platforms. The cleaning process narrowed down 15,461 comments to 2,650, which were then analysed using thematic, emotion and sentiment analysis techniques.

The thematic analysis revealed that virtual tourism evokes a complex range of public beliefs. While many express awe and excitement toward its immersive capabilities, others remain sceptical about authenticity compared to physical travel. Additional themes show people draw comparisons to real-world tourism, discuss technology’s role and note educational value and novelty. However, some comments raise concerns about potential societal harms, exploitation and mental health impacts. Sentiment analysis found over half of the comments positive, though some were negative. Emotion analysis showed contentment, happiness and excitement as most frequent, though sadness, worry and loneliness also featured. Overall, perceptions of Metaverse tourism encompass enthusiasm yet substantial ambivalence.

To the best of the authors’ knowledge, this study is one of the first to comprehensively analyse public discussions on Metaverse tourism. It takes TAM and Rogers’s DIT a step further and provides fresh insights into how these theories can be employed in the emerging field of Metaverse tourism. The themes revealed new conceptual insights into multidimensional factors shaping public beliefs about Metaverse tourism and thus informing scholarly research on virtual interaction and technology acceptance regarding Metaverse tourism. In addition, the results can help tourism providers, platforms and marketers address salient public beliefs and sentiments/attitudes in developing marketing offerings, experiences and communications. Over time, this analysis methodology can be used to track the evolving public perceptions of Metaverse tourism.