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This study aims to investigate disclosure of asbestos-related liabilities in corporate accounts and counter-accounts to examine whether and how accounting contributes to corporate accountability for asbestos-contaminated products.

This study uses the Goffmanesque perspective on impression management to examine instances of concealed asbestos-related liabilities in corporate accounts vis-à-vis the revealing of such liabilities in counter-accounts.

The findings show counter-accounts provide significant information on liabilities originating from the exposure of employees and consumers to asbestos. By contrast, the malleability of accounting tools enables companies to eschew accounting disclosures. While the frontstage positive performance of companies served an impression management role, their backstage concealing actions enabled companies to cover up asbestos-related liabilities. These companies used three categories of mechanisms to avoid disclosure of asbestos-related liabilities: concealing via a “cloak of competence”, impression management via epistemic work and a silent strategy of concealment frontstage with strategic reorganisation backstage.

This study has policy relevance as regulators need to consider the limits of corporate disclosures as an accountability tool. The findings may also initiate academic and practitioner conversations about accounting standards for long-term liabilities.

This study highlights the strategies companies use both frontstage and backstage to avoid disclosing asbestos-related liabilities. Through analysis of accounts and counter-accounts, this study identifies the limits of accounting as an accountability tool regarding asbestos-induced diseases and deaths.

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.

This study aims to assess the extent to which Uganda university libraries have implemented digital transformation technologies and to determine the facilitators and barriers affecting the implementation of digital transformation in selected university libraries in Uganda.

This study used a convergent parallel mixed methods design. It was conducted in six selected university libraries in Uganda, which were in three private and three public universities. The study sample included 103 librarians with a minimum qualification of a bachelor’s degree and six library directors.

The findings indicated that there was an average (n = 37, 48.7%) implementation of digital transformation in the selected university libraries in Uganda. Some of the barriers hindering digital transformation included inadequate funding, lack of awareness of digital technologies, inadequate ICT skills, insufficient ICT infrastructure and limited staff among others. There is a need for library management to provide support in the form of funds, policies and human resources to implement such digital transformation.

The criteria for choosing universities were those that have been around for at least 10 years. The reason for this was that it was assumed that these universities would have well-established staff development programmes and procedures as well as be likely to have incorporated technology into their services, including libraries. This study’s limitations stem from the fact that this criterion for selection might not apply to all Ugandan university libraries, particularly those that are less than 10 years old and may not have been well represented in this study.

The magnitude of the problem of digital transformation in university libraries in Uganda is unclear because of the limited research available in the Uganda library and information science field. This study presents the status of digital transformation in Uganda university libraries.