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Using critical disaster studies and state theory, we assess the disaster aid platform named Lebanon Reconstruction, Reform and Recovery Framework (3RF) that was put in place by international donors in the aftermath of the Beirut Port Blast in August 2020, in order to examine the effectiveness of its inclusive decision-making architecture, as well as its institutional building and legislative reform efforts.

The paper uses the case study approaach and relies on two original data sets compiled by authors, using desk reviews of academic literature and secondary data, in addition to 24 semi-structured expert interviews and participant observation for two years.

The aid platform appears innovative, participatory and effectively functioning toward recovery and reform. However, in practice, the government dismisses CSOs, undermines reforms and dodges state building, whereas the 3RF is structured in incoherent ways and operates according to conflicting logics, generating inertia and pitfalls that hinder effective participatory governance, prevent institutional building, and delay the making of projects.

The research contributes to critical scholarship as it addresses an important research gap concerning disaster aid platforms’ institutional design and governance that are under-studied in critical disaster studies and political studies. It also highlights the need for critical disaster studies to engage with state theory and vice-versa.

The research contributes to evaluations of disaster recovery processes and outcomes. It highlights the limits of disaster aid platforms’ claims for participatory decision-making, institutional-building and reforms.

The paper amplifies critical disaster studies, through the reflexive analysis of a case-study of an aid platform.

The purpose of this study is to identify the key components pertaining and governing a Computer-Generated Influencer’s (CGI’s) identity and explores and analyzes the ensuing relationship between the CGI and its digital environment.

This study follows an exploratory approach using in-depth interviews of CGI followers. A total of 37 in-depth interviews were then analyzed using an inductive thematic approach to steer data coding.

CGIs are considered as brand entities that have a combination of components under their overall perceived identity. This study encompasses the different relational dimensions, whether from a follower’s followers, CGI-follower’s, CGI–human influencer’s or CGI-endorsed brand’s perspective.

This research contributes a seminal work in the field of virtual influencers.

The paper aims to investigate how accounting techniques, when embedded within data-driven public-sector management systems, mask and intensify the neoliberal ideological commitments of powerful state and corporate actors. The authors explore the role of accounting in the operationalisation of “instrumentarian power” (Zuboff, 2019) – a new form of power that mobilises ubiquitous digital instrumentation to ensure that algorithmic architectures can tune, herd and modify behaviour.

The authors employ a qualitative archival analysis of publicly available data related to the automation of welfare-policing systems to explore the role of accounting in advancing instrumentarian power.

In exploring the automation of Australia's welfare debt recovery system (Robodebt), this paper examines a new algorithmic accountability that has emerged at the interface of government, technology and accounting. The authors show that accounting supports both the rise of instrumentarian power and the intensification of neoliberal ideals when buried within algorithms. In focusing on Robodebt, the authors show how the algorithmic reconfiguration of accountability within the welfare system intensified the inequalities that welfare recipients experienced. Furthermore, the authors show that, despite its apparent failure, it worked to modify welfare recipients' behaviour to align with the neoliberal ideals of “self-management” and “individual responsibility”.

This paper addresses Agostino, Saliterer and Steccolini's (2021) call to investigate the relationship between accounting, digital innovations and the lived experience of vulnerable people. To anchor this, the authors show how algorithms work to mask the accounting assumptions that underpin them and assert that this, in turn, recasts accountability relationships. When accounting is embedded in algorithms, the ideological potency of calculations can be obscured, and when applied within technologies that affect vulnerable people, they can intensify already substantial inequalities.