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The purpose of this paper is to provide a theoretically informed analysis of the evolution of environmental management accounting (EMA) and social and environmental reporting (SER), and the accompanying development of a sustainability programme, in a large family-owned, unlisted corporation.

A longitudinal case study based on semi-structured interviews and documentary data was conducted. The main periods of fieldwork were carried out in 2007 and between 2010 and 2012. Sustainability reports were collected until 2019 when SER appeared to cease. The case analysis draws on the concepts of organisational identity (OI) and internal legitimacy (IL) to examine the decision-making and actions of a range of key organisational actors as they engage with EMA and SER.

The study demonstrates that a gap between an organisation’s identity claims (“who we are”) and its enacted identity (“what we do”) can enable the adoption of constitutive, performative and representational EMA and SER. It illuminates the nature of the role of key actors and organisational dynamics, in the form of OI and IL, in adapting these practices. It also demonstrates that, in giving meaning to the concept of sustainability, organisational actors can draw on their organisation’s identity and construct the comprehensibility of an organisational sustainability programme.

More empirical work is needed to examine the applicability of OI and IL to other settings. It would also be beneficial to examine the potential for OI work to allow organisations to change and reinvent themselves in response to the evermore pressing environmental crisis and the role, if any, of EMA in this process.

The study enriches our understanding of why and how EMA and SER evolve by demonstrating that paying attention to OI and IL can provide further insight into the decision-making and actions of organisational members as they recognise, evaluate, support and cease these practices.

Higher levels of participation in school are linked to greater academic performance, better health and well-being and positive long-term outcomes for young people. Evidence shows that for students with emotional and behavioural difficulties (EBD), participation in school-based occupations is often restricted in comparison to their peers. Given the recent advancements towards introducing a new model of school-based occupational therapy in Ireland, this paper aims to discuss how occupational therapy can support students with EBD to increase their participation within the post-primary school context. The opinions in this paper are derived from the authors’ experience in the development of this practice in the Republic of Ireland.

The authors reviewed current literature and reflected on current practice to describe the unique role of occupational therapy in supporting students with EBD in the school environment.

Occupational therapists have potential to play a key role in school-based support for students with EBD. The authors describe how occupational therapists can promote whole school understanding of EBD and enable skill development, self-regulation, participation and school belonging, among youths with EBD. There is a significant lack of literature guiding practice in this area. Further research is required to explore professional issues and identify best practice.

This paper aims to provoke consideration of how school-based occupational therapists can play a crucial role in supporting students with EBD who are otherwise at risk of occupational injustice.

The paper aims to expand on the works well documented by Joy Boulamwini and Ruha Benjamin by expanding their critique to the African continent. The research aims to assess if algorithmic biases are prevalent in DALL-E 2 and Starry AI. The aim is to help inform better artificial intelligence (AI) systems for future use.

The paper utilised a desktop study for literature and gathered data from Open AI’s DALL-E 2 text-to-image generator and StarryAI text-to-image generator.

The DALL-E 2 significantly underperformed when it was tasked with generating images of “An African Family” as opposed to images of a “Family”. The pictures lacked any conceivable detail as compared to the latter of this comparison. The StarryAI significantly outperformed the DALL-E 2 and rendered visible faces. However, the accuracy of the culture portrayed was poor.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further. The implications, however, are that more inclusion is warranted to help address the issue of cultural inaccuracies noted in a few of the paper’s experiments.

The paper is useful for advocates who advocate for algorithmic equality and fairness by highlighting evidence of the implications of systemic-induced algorithmic bias.

The reduction in offensive racism and more socially appropriate AI can be a better product for commercialisation and general use. If AI is trained on diversity, it can lead to better applications in contemporary society.

The paper’s use of DALL-E 2 and Starry AI is an under-researched area, and future studies on this matter are welcome.