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Purpose

The purpose of this research is to characterise governance in the education domain, examining the Australian school sector. In addition to investigating the role of accounting at a distance in programmes of governance, as has been the case in extant accounting research, we also seek to understand how so-called intimate accountings (Asdal, 2011) act on distance through the instantiation of situationally meaningful, local and embodied forms of calculation permeating everyday practices. In so doing, we highlight that governance is more than a top-down hierarchical process, relying also on everyday actors producing local calculations that help “align” (Miller, 2014) various calculative infrastructures of (educational) governance.

Design/methodology/approach

A case study design is employed, focusing on Australian schools. Data collected include 35 semi-structured interviews, field observations and archival documents. Our case study explores how accounting practices and calculative tools for managing school performance are implemented across different schooling contexts, and how these tools are understood by individuals interacting with them. Data analysis examines how accounting systems and everyday practices of accounting and calculation play a role in governance, culminating in the typification of the notion of cascading governmentality.

Findings

We find that MySchool, a prominent tool for educational accountability in Australia, is situated in cascading translations of governmentality, involving global, national and local actors, constitutive of, and constituted by, processes of accounting intimacy. We find that processes of governmentality require a multiplicity of actors and intimate accounting (Asdal, 2011) calculations – the “nitty-gritty”, everyday accounting practices of government agencies, schools, parents, school children and members of the community – making the programmatic reform of the Australian education sector (the so-called “the education revolution”) “fit” and work.

Practical implications

Our study calls for policymakers to consider the relational impacts of accountability systems, suggesting that local-level actors are not mere subjects of policy but also active participants in constructing governance. We also emphasise a need for more awareness of the emotional and relational consequences of accounting systems, particularly in domains such as education shaping family life and local communities.

Originality/value

We make four contributions to the extant literature. First, we challenge the traditional view of governmentality as a top-down, state-initiated policy agenda (Ahrens et al., 2020; Neu, 2000; McKinlay and Pezet, 2010), proffering instead the notion of cascading governmentality. Second, we demonstrate how governmentality is enacted locally through intimate accounting practices. Third, we show the unintended effects of accounting intimacy, contributing to ongoing discussions concerning accounting’s role in acting from and on distances (Corvellec et al., 2018; Quattrone and Hopper, 2005; Robson, 1992). Fourth, we empirically contribute to the small but growing body of accounting research focused on education (Cutler and Waine, 2004; Edwards et al., 1999; Edwards et al., 2000; Groff et al., 2010; Levacic, 1990; Neu, 2006; Rubin, 2004; Unda et al., 2023), encouraging further comparative, cross-national research exploring the intersections of accounting practices and educational governance.

A pervasive legacy of neoliberalism has been the centrality of accounting inscriptions in governance practices. The use of accounting calculations and numbers, particularly in the form of performance metrics and key performance indicators, has flourished under the influence of New Public Management (Hood, 1995). Policy work and its associated efforts are predominantly assessed by comparing quantitative goals with quantified outcomes. Correspondingly, accounting has achieved and maintained a position of considerable significance in this process via the exercise of cost–benefit analysis (Lohmann, 2009), value-added accounting (Burchell et al., 2013), standard costing (Jeacle, 2003), systems of ranking and performance evaluation (Kornberger and Carter, 2010; Pollock and D’Adderio, 2012; Pollock et al., 2018), and other calculative means of representing and measuring economic activity and societal impact (Buallay, 2019; Hussain et al., 2018). Further, such calculative practices have attained a central role in educational governance in many countries, including Australia (Unda et al., 2023), Canada (Neu, 2006), Singapore (Tan, 2008), the United Kingdom (UK) (Cutler and Waine, 2004; Edwards et al., 1999, 2000; Levacic, 1990) and the United States of America (USA) (Groff et al., 2010; Rubin, 2004).

A prominent example of the thrall of accounting systems in the domain of educational governance is the large-scale collection of school performance information. In Australia, the country of interest in our study, such information is aggregated and published online via the MySchool website (hereafter MySchool). MySchool, comprising key inscriptions informing public sector accountability and educational measurement, collects, analyses and disseminates accounting information on the performance and characteristics of Australian schools, their management, and the profiles and accomplishments of students. In line with prior research focusing on accounting inscriptions enabling action at a distance (Miller, 1991; Robson, 1992), inscriptions within MySchool exemplify a “strong mixture of mobile, stable and combinable qualities”, providing “a form of knowledge that may have greater potential for power or action at a distance than many others” (Robson, 1992, p. 701). In the case of MySchool, as demonstrated below, the drive behind various techniques of recording, monitoring, tracking, analysing and other practices of accounting and numbering lies in the production of a knowledge infrastructure (Edwards, 2010; Karasti et al., 2016) shaping decision-making and policy actions.

Extant accounting literature, analysing the ability of inscriptions to enable action at a distance, tends to invoke a “linear” translation of knowledge (Quattrone and Hopper, 2005) – be it geographic, functional or even spiritual (see Corvellec et al., 2018). Translations move from one context to another, affecting the control of actions and allocation of resources, monitoring and intervening in activities in the name of improved management. This presumption has been recently challenged by a handful of accounting scholars arguing that distances are relational. From this perspective, distances “do not pre-exist, but result from existing relationships – among people, material artifacts, and abstract conceptions, for example” (Corvellec et al., 2018, p. 58). This renewed understanding has allowed Corvellec et al. (2018) to convincingly demonstrate that acting at a distance also depends on how accounting inscriptions act on distances.

To explain “what inscriptions do to distance” (p. 57), Corvellec et al. (2018) analysed accounting inscriptions in the context of public sector waste management, arguing that accounting inscriptions do more than serve as expressive supports of centralised control and governance. Rather, accounting inscriptions – in the form of invoices for food waste collection – enacted localised forms of control and governance, actively corralling citizens into practices of governance. Invoices, showing waste weights and costs, brought residents closer to their waste, incentivising them to better sort their garbage. Accordingly, waste invoices reduced the distance between residents and the (Swedish) government’s environmental and political goals. As such, Corvellec et al. (2018) characterised distance a consequence of (rather than a prerequisite for) accounting, introducing the concept of “distance work” – a process interlinking environmental policies and economic management to households via waste collection invoices.

While Corvellec et al.’s (2018) study characterises distance work as a product of implementing top-down inscriptions, Miller (2014) cautions us that “calculative infrastructures” [1] “have been made to fit, and we need to pay attention to the ways in which they have come to be aligned” (p. 46). Thus, our paper is motivated by a desire to better understand the often complex and manifold processes through which economic systems and accounting practices become interconnected in the context of Australian educational governance. By investigating how calculative infrastructures (ranging from regulatory frameworks, programmes and technologies of government, and management practices) align with one another, we provide important insights into the dynamics of contemporary (Australian) economic life. We argue that such relations require an alignment of both action at a distance (i.e. distant accounting) and action on distances (i.e. intimate accounting).

While Corvellec et al. (2018) allude to the importance of processes acting on distances, we focus on this significant but overlooked phenomena by mobilising the concept of intimate accounting. We argue that accounting's ability to make action at a distance work is increasingly complemented by everyday practices of intimate accounting acting on distances. The notion of intimate accounting was proffered by Asdal (2011). Asdal contends that policy performance is “secured, not by action at a distance, but by nitty-gritty accounting” (p. 5). In a study of environmental pollution in Norway, she shows how a government pollution control agency sought to gain power through various quantification practices. However, when the numbers alone did not confer authority on the agency, it became necessary to link its pollution control objectives to broader societal concerns associated with the vulnerability of nature. Then, the quantification practices and priorities of the pollution control agency began to impact factory practices. Pollution control was no longer an abstract, distant and disembodied construct. Rather it became a situationally meaningful, local and embodied practice – that is, a form of intimate accounting drawing policy into proximate everyday calculative practices.

Our case study of MySchool builds on Asdal's (2011) concept of accounting intimacy. We show how “nitty-gritty” or situationally meaningful, local and embodied forms of accounting are accomplished in educational governance, rearranging relations between actors (e.g. parent–child relations mediated by spreadsheets), creating new intimacies (e.g. parents engaging with a school and their child via digital portals) and enrolling unexpected actors (e.g. real-estate agents using school performance data as part of their marketing strategies). This alignment of intimate accountings with the programmatic reform of the Australian education sector (the so-called “education revolution”) has been accomplished via what we characterise as cascading translations of governmentality. These cascading translations of governmentality interconnect calculations of global, national, state, organisational and individual actors, mediating relations between politicians, policymakers, schools, parents, students and the public. In comparison to extant accounting literature viewing governmentality as a way for governments, government entities and institutions to govern a populace (Neu, 2000), we show that everyday actors are intricately interconnected to the shape and shaping of neoliberal frameworks of governance. Cascading translations of governmentality interconnect a multiplicity of actors and calculations in the same social times and spaces – or (govern) mentalities.

We also find that the implementation of programmes of government, translated into technologies of government such as MySchool, can have profound consequences on the lives of everyday actors, even beyond the domains of intended governance. Previous accounting studies have explored the link between macro-level government policies and accounting practices in traditional economic domains, such as profit-oriented organisations (Miller and O’Leary, 1987), as well as emerging knowledge-intensive public organisations (Grossi et al., 2020), such as universities (Aliabadi et al., 2021; Dobija et al., 2019; Lawrence and Sharma, 2002) and schools (Bracci et al., 2024; Firtin and Kastberg, 2020; Tooley and Guthrie, 2007). In comparison, we broaden this research by examining the spillover and unintended effects of accounting calculations (in an educational context). We find educational governance has unintended effects profoundly affecting familial relationships and a host of everyday decisions (such as where families choose to live, what school parents select for their children and subjects that students elect to study).

Against this backdrop, our paper makes four main contributions to the literature on accounting and governmentality. First, our paper provides analytical insight into how a calculative infrastructure has been made to fit and align in practice (Miller, 2014). Rather than providing a traditional view of governmentality as the formulation and implementation of top-down, state-initiated policy agendas (Ahrens et al., 2020; Neu, 2000; McKinlay and Pezet, 2010), we introduce the notion of cascading translations of governmentality. There is a multiplicity of translations of policy (in our case, giving structure and meaning to an education revolution). It is through the mutually constitutive nature of these multiple, cascading translations that the calculative infrastructure of Australian school education is made to align and function. Second, we demonstrate how governmentality is enacted locally through intimate accounting practices, whereby abstract, distant and disembodied policy becomes intimately connected to, and mutually constituted by, situationally meaningful, local and embodied practices. We show how these practices (re)shape relationships, such as parent–child dynamics, influencing decisions affecting actors within and beyond the education system. Third, our research expands previous studies on the connections between macro-level policies and accounting by exploring the unintended effects of governance (Burchell et al., 2013; Miller, 1991; Wickramasinghe et al., 2021). For example, attempts to measure and monitor school performance have had profound but unintended consequences. Such consequences include significant increases in real estate prices in the catchment areas of high performing, no-fee government schools, major changes in the routines of families (e.g. children traveling long distances each day to attend desirable private schools (Burke and Yan, 2019), building the costs of private tutoring into family budgets (McDougall, 2014), and teachers focusing on educational activities related to national testing to the exclusion of other learning opportunities (Tomazin, 2013). Fourth, our case makes an empirical contribution to the small but growing accounting literature on education (Cutler and Waine, 2004; Edwards et al., 1999, 2000; Groff et al., 2010; Levacic, 1990; Neu, 2006; Rubin, 2004; Unda et al., 2023). Whilst our case focuses on education in Australian schools, educational governance is also a matter of concern in other countries, such as the UK, USA and Singapore. Our case is of comparative interest and may help pique interest in cross-national studies and other areas of germane research, as discussed in the conclusion of our paper.

The remainder of our paper is organised as follows. Section 2 outlines literature informing our understanding of accounting and neoliberal governmentality, as well as distant and intimate accounting. This is followed by a presentation of our research methods in Section 3. Section 4 contains a brief overview of the Australian Education Revolution, followed by examples of intimate accounting practices found in our case study. Section 5 discusses the case and concludes by outlining its practical implications and suggestions for future research.

Our paper is grounded in the governmentality literature. Introduced by Michel Foucault in the 1970s (see Burchell et al., 1991), the concept of governmentality has been developed across various disciplines, including accounting, critical sociology and political geography (see Chiapello, 2017; Rose et al., 2006; Sharma and Irvine, 2016; Wickramasinghe et al., 2021). The concept of governmentality, derived by linking “governing” and “mentality”, characterises how we conceptualise governance. Central to this approach is the idea that our representations of reality are closely tied to how they are acted upon and governed. Thus, the concept of governmentality is more expansive than a consideration of governments. While states are important, they are not the sole centre of power. Governance, therefore, operates not only within geographical and territorial boundaries but also in spaces shaped by the circulation of accounting devices, inscriptions and technical practices (Mennicken and Miller, 2012).

After establishing a connection between accounting and governmentality, primarily through seminal articles by Miller and Rose (1990) and Miller and O'Leary (1987), a steady stream of related research has followed (Ahrens et al., 2020; Brivot and Gendron, 2011; Graham, 2010; Kurunmaki and Miller, 2006, 2011; McKinlay and Pezet, 2010; Mennicken and Miller, 2012; Sharma and Irvine, 2016). More recently, research has increasingly focused on the relationship between accounting and neoliberalism as a particular form of governmentality (see Andrew and Cahill, 2017; Ellwood and Newberry, 2007; Fourcade and Healy, 2013; Jupe and Funnell, 2015; Morales et al., 2014; Rose, 1991). Notably, critical accounting research has emphasised how accounting techniques naturalise neoliberal forms of governance. A recent critical review of accounting and neoliberalism finds that researchers typically explore neoliberalism using one of three approaches: (1) as a phase of capitalism, (2) as discourse and (3) as a form of governmentality (Chiapello, 2017). From the first perspective, neoliberalism is understood as the “new capitalism,” a strategy adopted to strengthen the position of the capitalist class and increase income (Harvey, 2005). From the second perspective, neoliberalism is conceptualised as a hegemonic ideology and rhetoric of Western society. Finally, neoliberalism can refer to changes in how Western governments manage the public sector, including the development of internal markets and the value-for-money provision of public services.

In our paper, we adopt Chiapello's (2017, p. 5) third approach, which “engages in dialogue with the Foucauldian tradition and views neoliberalism more broadly as a manifestation of liberal governmentality”. We use a Foucauldian lens as it provides a critical framework for understanding how neoliberalism shapes not only economic policies but also individual behaviours and societal norms. By focusing on the concept of governmentality, this approach highlights how neoliberalism extends traditional economic models, considering the influential ways people govern themselves and others, with this revealing the deeper power dynamics and mechanisms of control in contemporary societies.

Relatedly, Foucault (2008) contrasted neoliberal governmentality with traditional forms of governmentality, such as disciplinary governmentalities (Foucault, 1977). Disciplinary governmentality focuses on self-regulation through the instillation of norms and standards. This form of governance is linked to the Panopticon, which encourages individuals to internalise norms and standards to manifest self-discipline. Neoliberal governmentality, however, governs human behaviour in more subtle and indirect ways. Neoliberal governmentality incentivises certain forms of behaviours (Foucault, 2008). Thus, neoliberalism as governmentality promotes a responsible and entrepreneurial self (Cooper, 2015; Gilbert, 2021) – a self that can be governed at a distance.

As a neoliberal governance tool or technology (Rose and Miller, 1992), accounting can be seen as a language with specific vocabularies and meanings tied to various modes of calculation (Miller and Napier, 1993). Accounting has the power to shape people's lives and influence the economic and social order of everyday life (Ezzamel et al., 2004; Mennicken and Miller, 2012; Robson, 1992). In this sense, accounting and its calculative practices possess a distinct performative quality (Christner and Sjögren, 2022; Firtin and Kastberg, 2020; Quattrone, 2009; Revellino and Mouritsen, 2015; Yu and Huber, 2023).

Due to its performative nature, accounting's specific calculative practices, along with its discursive and verbal representations (Frezatti et al., 2014; Malmmose, 2015; Miller and Napier, 1993), makes visible certain areas, events and processes. As such, accounting inscriptions and calculative practices (be they rankings, performance measures, costs or financial ratios) construct realities (Ezzamel and Hoskin, 2002; Miller, 2001; Pollock and D’Adderio, 2012). These realities influence people to act in certain ways (Espeland and Sauder, 2007; Ezzamel, 2012; Kornberger and Carter, 2010; Pollock et al., 2018). Accounting also plays a role in shaping both abstract and physical spaces, defining the identities of those who inhabit them (Mennicken and Miller, 2012), creating new spaces of representation along with new logics and practices (Brown and Dillard, 2015).

In the context of neoliberal governmentality and the education sector, rankings serve as powerful accounting inscriptions, not only quantifying performance but also governing behaviour (Lynch, 2015; Parker, 2022). Rankings are calculative tools rendering visible schools' relative performance (Pollock and D’Adderio, 2012), creating a system of evaluation (Reinstein and Calderon, 2006) influencing decision-making among a range of actors – such as educators, parents, policymakers and students. These rankings align with a broader neoliberal agenda by fostering competition and accountability (Espeland and Sauder, 2016; Nunes et al., 2015); schools are incentivised to meet specific, standardised performance metrics to maintain or improve their rankings. The performative nature of rankings not only reflects but also shapes educational practices, imposing external measures of success that can override local contexts and priorities (Espeland and Sauder, 2007; Pollock et al., 2018). This performativity reinforces a shift towards market-driven values in education, where schools and their stakeholders act in ways that are governed by rankings, responding to their influence as if they were objective truths (Marginson and Van der Wende, 2007).

Thus, the performative power of rankings not only shapes behaviours and identities (Mennicken and Miller, 2012) but also introduces a form of “distance” between those being ranked and the evaluative criteria used to assess them. In the extant accounting literature, distance is used as an analytical concept to refer to physical or geographical space (Preston, 2006; Preston et al., 1997), differences between business units or organisational levels (Asdal, 2011; Miller, 1991; Quattrone and Hopper, 2005) or, more abstractly, to differentiate between contexts (Qu and Cooper, 2011). Thus, distance typically signifies when an actor is removed from the interests of a given activity or action.

In a study exploring connections between accounting and distance, Quattrone and Hopper (2005) examined the implementation of an enterprise resource planning (ERP) system in two international firms. By focusing on how implementation relates to management control and distance, Quattrone and Hopper (2005) challenged the assumption that accounting inherently and unproblematically reduced distance, instead arguing that there is “a complex process involving inscriptions, translations, beliefs, mediation, accounting and information processing technologies” (p. 761) between control and distance. Building on Quattrone and Hopper's (2005), Corvellec et al. (2018) used the concept of topology to explore how “inscriptions affect distance” (p. 2), introducing the notion of “distance work”. Invoices for the weight of unsorted garbage linked Swedish households to neoliberal environmental policies aimed at connecting the economy and the environment via waste management practices. Here, distance work fostered proximity between households and policymakers, making possible both control and the enrolment of actors into this governance process. Thus, Corvellec et al. (2018) view distance as an effect of accounting rather than a precondition of its operation. To Corvellec et al., “inscription devices define distances” (p. 64).

However, as Miller (2014, p. 46) notes, when various calculative devices shaping the economy and economic relations align, as in the study of Corvellec et al. (2018), it is because they have been made to “fit”. As researchers, it is important that we examine how this alignment occurs. It is our view that governmentality is made to align and work through processes of intimate accounting.

Asdal (2011) contrasts “distant accounting” – where regulation and control are exercised from afar through abstraction and centralised modes of calculations – with “accounting intimacy” (p. 6). Her study of pollution regulation highlights a more intimate form of governance where control was not imposed only from a distance but also through direct engagement between a government agency and individual factories. This process was mediated by shared “technical interests” (Asdal, 2011). There was a shift from “action at a distance” to “intimate action”, highlighting how power-knowledge, once exercised through centralised authority, shifted to more “intimate” calculative practices enacted in situ, close to the actions being measured and regulated.

In summary, accounting numbers and calculative practices surrounding neoliberal policy and governance have been a long-standing area of accounting research. Governments use accounting inscriptions as technologies articulating and implementing programmes, which accounting researchers have shown enable action at and on distances, generating and (re)shaping both organisational activities and individual behaviours. Yet, the intimate forms of accounting mobilised in everyday life, through actors’ interactions with accounting numbers and inscriptions, have been largely overlooked by accounting scholars. And this is a matter of increasing importance, given that intimate forms of accounting help us understand how various actors navigate economic systems and broader social structures.

The theoretical concepts of distant accounting and intimate accounting are deeply interconnected and inform governance in contemporary society. Neoliberal governmentality, as articulated through Foucault's lens, provides the broader framework for understanding how governance and power operate not through direct control, but by shaping individuals' behaviours and decisions through subtle and indirect methods. Distant accounting functions as one of these methods, using abstract calculative practices to govern at a distance, aiming to align a range of various actors with neoliberal values. However, as actors seek to make sense of these abstract practices, governance becomes more situationally meaningful, local and embodied through the instantiation of everyday practices. Correspondingly, what Asdal has called intimate accounting emerges. Together, these concepts illustrate the dynamic and evolving ways in which accounting practices govern at and on distances, shaping the macro-level structures of neoliberalism and the micro-level interactions of everyday life. To summarise, Table 1 outlines the main theoretical concepts used in this paper (neoliberal governmentality, distant accounting and intimate accounting) to illustrate their interrelations and distinctions.

Table 1

Summary of conceptual relationships between neoliberal governmentality, distant accounting and intimate accounting

ConceptDefinitionIllustrative references
Neoliberal governmentalityA mode of governance wherein power is exercised indirectly, shaping individual choices and behaviours through norms, incentives, and responsibilities. Neoliberal governmentality governs by promoting self-regulation, responsibilisation and the promotion of the entrepreneurial selfFoucault (1977, 2008), Miller (2014), Miller and Rose (1990), Miller and O’Leary (1987) 
Distant accountingAccounting practices using abstract, standardised metrics to manage and control entities from a distance. Distant accounting governs via impersonal, disembodied, calculative measures materialising programmatic goalsRobson (1992), Quattrone and Hopper (2005), Corvellec et al. (2018) 
Intimate accountingSituationally meaningful, localised, and embodied accounting practices that engage individuals with programmatic goals, acting on distance. Intimate accounting governs through everyday practicesAsdal (2011) 
Source(s): Table created by authors

These concepts are mobilised in response to observations that governments have moved towards indirect forms of intervention (i.e. governing at a distance), relying on multiple information flows (see, for example, Broadbent and Laughlin, 2013). What has been overlooked, however, is how everyday actors (co)produce these information flows. Our paper aims to address this gap by tracing these everyday calculations and inscriptions within the Australian education sector.

Our research is based on a qualitative study of the Australian education (school) sector. Australia was chosen for three reasons. First, neoliberalism is a dominant governing rationality in Australia (Beeson and Firth, 1998; Connell, 2013). The Australian education sector functions as a neo-liberal rationality heavily informed by market logic, entrepreneurship and consumer (parent/student) choice (Marginson, 1997). This offers an ideal site to investigate how accounting is implicated in these economically informed choices.

Second, the Australian neoliberal political project views education as an investment in human capital, creating competitive advantage for future national economic benefit and prosperity. Also, as a nation, Australia governs “at a distance” (Miller and Rose, 1990, p. 14; Neu and Graham, 2006; Preston et al., 1997). The Australian government controls its citizens through rationalised devices and technologies including statistics, measurement, forecasting, public performance management systems and big data. Thus, Australia provides a relevant context and rich source of data for this study.

Third, the Australian government has shifted its traditional responsibilities for social problems, such as unemployment and illness, to problems for self-management (e.g. providing tax incentives for the uptake of private health insurance). Australian society has reorganised social relations around the notion of “enterprise” (McNay, 2009, p. 58). Consequently, areas such as education are increasingly becoming matters of personal choice and provision by citizens. This construction of “responsible citizens” (Rose, 1999, p. 41) provides opportunities to trace a wide range of calculative technologies, systems and actors facilitating this neoliberal programme of responsibilisation for future productivity and economic growth.

Data from this domain were collected over a period of three years, from 2016 to 2019. As Table 2 illustrates, a total of 35 interviews with a range of actors from the Australian school sector were conducted. Interviewees included principals, teachers, parents, students [2], school board members, educational consultants and school psychologists. Purposeful sampling was used to select the initial interviewees (the “seeds”), who both fitted the research criteria and enabled substantive and relevant learnings about the sector. Subsequent interviewees were identified via snowball sampling (Parker et al., 2019). Here, preliminary interviewees were asked to identify other potential interviewees relevant to this research project. The latter were then invited to participate in this research. All interviews were semi-structured and lasted between half-an-hour and two hours in duration. A copy of the interview guide is available on request.

Table 2

Interview summary

Interview detailsNumber
Total number of interviews35
Total interview duration1,878 minutes (31.3 hours)
Average interview duration54 minutes
Total number of interviewees35
Total number of groups represented5
Summary of interviewees by group 
Principal6
Teacher11
Parent9
Students (above the age of 18 years old)6
Others (Educational consultants, School Psychologist, School Board Member3
Source(s): Table created by authors

In addition to face-to-face interviews, primary digital data were collected. These included information from digital platforms (including Facebook and Twitter accounts) of the government and its agencies, such as the Australian Curriculum, Assessment and Reporting Authority (ACARA) and the Australian Institute for Teaching and School Leadership (AITSL), international agencies such as the Organisation for Economic Co-operation and Development (OECD), World Bank and other educational actors. Government records (such as parliamentary proceedings [Hansard], bills, acts, policies, treaties, and census data) and school records (such as teaching reports, student report cards, school annual reports, and school newsletters) were also collected. To supplement these primary sources of data, various secondary data were collected, including media reports and video clips from the news, current affair programs and YouTube media. These data were collected to provide contextual understanding, triangulate interviews, and situate and validate the study's findings (Flick, 2018; Silverman, 2010).

Data were analysed using NVivo, a qualitative data analysis program. NVivo codes data line by line using categories the researcher constructs during the inductive and iterative process of coding field observations. All interview transcripts were coded in NVivo by the lead author. The coding scheme involved assigning codes or “nodes” to specific text to identify patterns, themes and relationships. These codes emerged inductively from the data and structured the data analysis, drawing connections to specific theoretical concepts guiding our analysis and findings.

Our coding was guided by the “constant comparative method” developed by Glaser and Strauss (1967) and involved two layers: (1) a within-interview analysis and (2) a cross-interview analysis (Yin, 2014). This approach, also referred to as initial coding (Charmaz, 2014), involved coding the data, comparing codes and data, and eventually condensing and refining codes into categories, categories into themes and finally themes into findings. Constant comparison continued until key and related categories were sufficiently saturated to provide a connection to how the mundane practices of accounting and calculation are implicated in the everyday governance of the Australian education sector. To clarify this process, Table 3 provides illustrative examples of the progression from first-order categories (direct quotes or interpretations from participants) to second-order themes (research-interpreted patterns) and, finally, to aggregate dimensions structuring our final theoretical insights.

Table 3

Illustrative coding structure

First-order concepts (participants' terminology and observations)Second-order themes (emergent patterns)Aggregate dimensions
“… the spreadsheet automatically calculated the students average and the grade. Also, would let you know what the ranking of the student was in your class but also in the year level …”Use of digital tools to standardise student assessment and rankingInscriptions
“In our school we have a whole range of data sets, NAPLAN results … Plans are then put in place … to make sure we're fixing up the deficiencies that we see in that data.”Strategic use of data for school performance managementInscriptions
“Parents have so many choices [regarding] what to do with their children. They can send them to the local public school. They can send them to a private school, which may be around the corner. It may be 200 miles away, or 200 kilometres away.”Market-oriented parental decision-making across geographical spaceDistance
“… my decision … I wanted them to be at a school that was in, say, the top 50 or 60 in New South Wales … we're paying to send them to a Catholic school. Their academic results aren't as good as the public school … The public school that my girls went to ranked 60 spots ahead of all the private girls' schools.”Ranking-driven school selection across sectors and locationsDistance
“… I monitor those kids … I can assess where they're at. Then I can put that data in.”Real-time individual student trackingAccounting Intimacy
“I can see their homework, what homework they get for each class. I can see it. I also have the opportunity to say, “Yes, they've done this,” so that they [teachers] know that I know that they've done it … I can actually see if my daughter's missed a period …”Parental surveillance and engagement with digital platformAccounting Intimacy
Source(s): Table created by authors

A subset of the final coding structure is shown in Figure 1. Codes related to “inscriptions” reflect the ways in which accounting practices are embedded in both organisational structures and individual behaviours, while codes associated with “distance” illustrates the mechanisms through which accounting governs at a distance. Additionally, the concept of “accounting intimacy” is reflected in the coding of personal interactions with accounting numbers and practices.

Figure 1
A flowchart shows the accounting assemblages in the Australian education sector.The flowchart consists of 16 text boxes. The first text box on the top right, labeled “Accounting Assemblages in the Australian Education Sector,” leads to the second and third text boxes on the lower left and lower right, labeled “Programmes of Government” and “Technologies of Government.” “Programmes of Government” leads to the fourth, fifth, and sixth text boxes below labeled “Economic,” “National Productivity,” and “O E C D.” “Technologies of Government” leads to the seventh and eighth text boxes labeled “Inscriptions and Calculations” and “Consequences.” “Inscriptions and Calculations” leads to the ninth, tenth, eleventh, twelfth, and thirteenth text boxes labeled “N A P L A N,” “I S C E A,” “School ranking,” and “Public.” “Consequences” leads to the fourteenth, fifteenth, and sixteenth text boxes labeled “Real estate,” “Student equity,” and “Teaching to test.”

Subset of final NVivo coding structure showing node hierarchy. Source: Figure created by authors

Figure 1
A flowchart shows the accounting assemblages in the Australian education sector.The flowchart consists of 16 text boxes. The first text box on the top right, labeled “Accounting Assemblages in the Australian Education Sector,” leads to the second and third text boxes on the lower left and lower right, labeled “Programmes of Government” and “Technologies of Government.” “Programmes of Government” leads to the fourth, fifth, and sixth text boxes below labeled “Economic,” “National Productivity,” and “O E C D.” “Technologies of Government” leads to the seventh and eighth text boxes labeled “Inscriptions and Calculations” and “Consequences.” “Inscriptions and Calculations” leads to the ninth, tenth, eleventh, twelfth, and thirteenth text boxes labeled “N A P L A N,” “I S C E A,” “School ranking,” and “Public.” “Consequences” leads to the fourteenth, fifteenth, and sixteenth text boxes labeled “Real estate,” “Student equity,” and “Teaching to test.”

Subset of final NVivo coding structure showing node hierarchy. Source: Figure created by authors

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Section 4 provides a description of our case study findings.

Concerns about Australia's declining international educational competitiveness became a major impetus for local policy changes within schools, including a renewed emphasis on education standards and quality (Connell, 2013; Gorur, 2018). Improving Australia's performance in global student assessments, such as the Programme for International Student Assessment (commonly referred to as PISA), emerged as a national educational priority, highlighted by former Prime Minister Julia Gillard:

… For Australia to be ranked as a top five country in the world in Reading, Science and Mathematics by 2025. And by the same year, for us to be ranked as a top five country in the world for providing a high-quality and high-equity education system … (Gillard, 2012)

This Top 5 ranking project culminated in the foundational reforms of 2008, known as the “Education Revolution” (Gillard, 2010). Australia's education revolution marked the introduction of a significant investment in new calculative practices. Historically, Australian schools had been the responsibility of state governments, rather than the federal government (Harris-Hart, 2010), with each state and territory having its own curriculum and assessments. A key aspect of this foundational reform was the introduction of new forms of responsibilisation and accounting mechanisms to hold states and territories more accountable. With this Education Revolution came a new era of accountability and transparency – key planks of the national policy agenda:

Clear accountability helps create a learning environment that encourages innovation and excellence from school leaders, teachers and students. It also means that students, parents and teachers have evidence they need to make informed choices … Access to timely and robust performance information is crucial … Clear reporting about the performance of public services is consistent with the Australian Government’s commitment to more open and transparent governance. (Australia Government, 2008, p. 31)

The political rationality of the Education Revolution introduced three key measures of accountability and transparency: (1) a nationwide standardised assessment, referred to as the National Assessment Program – Literacy and Numeracy (NAPLAN), which was developed and managed by an independent statutory authority – the Australian Curriculum, Assessment and Reporting Authority (ACARA); (2) the creation of the Index of Community Socio-Economic Advantage (ICSEA), which allowed comparisons between schools with similar student populations; and (3) the launch of the publicly accessible “MySchool” website, wherein each school shares a range of information, including its NAPLAN performance, both in absolute terms and in comparison with other “statistically-similar” schools based on ICSEA. As we show below, the objective of these accounting and accountability numbers was to provide detailed information about the performance of all Australian schools – via the standardisation of education.

4.1.1 Standardisation of education – NAPLAN, ACARA, ICSEA, MySchool

To standardise education in Australia, NAPLAN was developed so that all Australian students could be assessed and compared using the same instrument and a single metric. Pre-NAPLAN, each Australian state and territory had its own student assessments, which did not allow easy comparison between schools from one state to another. NAPLAN is administered annually to students in years 3, 5, 7 and 9. Such testing typically occurs in May via a series of online or paper-based assessments in reading, writing, language conventions and numeracy. ACARA is responsible for overseeing the development, implementation and management of NAPLAN, ensuring its administration across schools in Australia.

While NAPLAN facilitated student comparisons, it was an inadequate tool for comparing schools. In response, the then Australian Prime Minister advocated for further calculations allowing comparison of “statistically similar” schools. This led to the development of a new calculation, ICSEA. ICSEA has been designed to provide a “fair” comparison of NAPLAN results between schools. It acknowledges research showing that family backgrounds (such as level of parents' education and household income) have a significant influence on student outcomes (ACARA, 2020). Based on their comparative social and educational advantage, schools are assigned a number on a scale from 500 to 1,300 (from lower to higher educational advantage), with the average ICSEA being 1,000.

The initial calculation of the Socio-Economic Advantage (SEA) in ICSEA was based on outdated 2006 Australian Bureau of Statistics (ABS)'s Population and Housing Census Data (ACARA, 2013). This resulted in significant criticism from the media, academics and various public and professional communities, claiming ICSEA was inaccurate and unreliable because it reflected the SEA of a student's area, not that of the individual student. In response, this calculation was revised to incorporate more “direct” data relating to parental education levels and occupations, as well as the proportion of students from Indigenous backgrounds or whose first language was not English. This information is provided by parents at the time of school enrolment (ACARA, 2020). The updated ICSEA scores allow more “meaningful” comparisons between a school and 60 “statistically similar” schools, i.e. schools having students with similar levels of educational advantage across Australia. This enables differences in student performances to be directly attributed to the effectiveness and quality of a school and its teachers.

NAPLAN and ICSEA results are made publicly available through the MySchool website, which has become central to national education policy by promoting and enabling consumer choice. In addition to NAPLAN results, every Australian school is required to present a detailed range of information in a standardised format on MySchool to help parents and members of the public understand the data. Parents are encouraged to familiarise themselves with MySchool and to personally inform themselves about the school(s) of their children.

When MySchool launched on January 28th, 2010, it made headline news across Australia, sparking intense interest and extensive public discussions in everyday social spaces. The Australian Prime Minister stated in her blog:

We expected it to be popular, but the level of interest has been beyond expectations. Everywhere I have been since January 28th, people have told me stories about conversations that MySchool has sparked. Conversations in workplaces and kitchens. Conversations between parents and school principals. Conversations between teachers in staff rooms. Conversations between parents and their children. (Gillard, 2010)

The numbers from the Education Revolution began to circulate more widely. Key inscriptions and calculations influenced discussions in everyday spaces, such as homes and offices, mediating interactions between various school actors including principals, teachers, students, parents and other stakeholders. While the NAPLAN and ICSEA scores on the MySchool website are akin to accounting numbers “enhanced by an abstract space enabling action at a distance” (Asdal, 2011, p. 5), the numbers generated in this process are individualised for the purpose of knowing and understanding each of the 10,000 schools in Australia. Like Asdal's (2011) factory, each school “was to report the results of their self-accounting” (p. 5), providing performance information addressing student attendance, NAPLAN scores and school finances. This “nitty-gritty” and detailed knowledge of the other, framed by and localising the mandates of policy, is what Asdal describes as “accounting intimacy” (Asdal, 2011, p. 6). Such intimate accounting is carried out and experienced by different actors connected within the Australian education sector. We discuss these actors below, starting with schools.

4.2.1 Schools

The public dissemination of NAPLAN results via the MySchool website has placed enormous pressure on schools to perform. This has also resulted in schools being openly questioned by parents and local communities when NAPLAN scores are poor compared to other “statistically similar” schools. Moreover, this task of intimate accounting around which MySchool is built means that individual schools and their staff are required to take responsibility for gathering the necessary data and organising it – using the standards, classifications and templates provided by ACARA. This is so data can be transported from local school sites and consolidated into relevant government “centres of calculation” (Latour, 1987, p. 232) – enabling governing at a distance. Such accounting intimacy – the local, nuanced and embodied connections that individuals and/or organisational participants have with accounting and/or performance information – has resulted in changes to and the introduction of new, whole-school practices that are highly responsive to, and a product of, this need to account for performance in terms of nationally framed measures.

For example, MySchool provides a template enabling schools to be evaluated against each other by creating relations of comparison and commensuration (Espeland and Stevens, 1998) between schools that were previously thought to be too dissimilar for comparison. Also, with the introduction of NAPLAN, state boundaries are no longer obstacles to (national) comparisons. As explained by a principal of a public school in regional Queensland:

… In context, if I was a private school principal at one of the poshest primary schools in Sydney, and in the next suburb over there's another really posh private school, and another really posh private school, I would want to see where my ranking was compared to them. We're in the same environment. We're competing to get students … There are so many impacts on that MySchool result. It did affect us. My school ranking is quite low and there are a lot of parents that say, I'm going to put my student [child] on a plane and send them to boarding school because we're not happy with the results of the school.” That was a barrier that we had to jump … It depends on how the parent values the MySchool website. Whether they take that as gospel for the quality of the education their kids are going to get. It's a constant battle, and I'd be lying if I said I didn't have parents take their kids out of my school because they thought they would get a better education elsewhere … Parents have so many choices [regarding] what to do with their children. They can send them to the local public school. They can send them to a private school, which may be around the corner. It may be 200 miles away, or 200 kilometres away. (Principal, Australian Public School)

As illustrated above, how schools understand their competition has changed. Where previously schools within the same category type or suburb considered one another as “competitors”, new accounting calculations stemming from NAPLAN and ICSEA have created competition between distant but “statistically similar” schools – as classified and displayed on MySchool. Thus, physically distant schools have become relationally closer to each other (Robson, 1992), intimately associated by accounting numbers and the calculations of NAPLAN and ICSEA. For example, in Figure 2, the school performance of a New South Wales private school is compared to not only a private school in the state of Queensland but a public school in the state of Western Australia.

Figure 2
A chart compares the NAPLAN scores (reading) of similar schools in 2016.The text at the top reads as follows: “‘Similar schools’” in this context are schools serving students from statistically similar backgrounds. The index of Community Socio-Educational Advantage (I C S E A) is used to group schools with students who have similar socio-educational backgrounds. For more information on I C S E A and the method used to identify statistically similar schools, visit the My School Glossary.” “This chart compares the average achievement of students from the selected schools with the average achievement of students at schools serving students from statistically similar backgrounds.” Above the chart, there are nine tabs from 2008 to 2016. The 2016 tab is currently selected. Below the tabs, fields for entering the school year, domain, and view mode with a submit button are shown. The details are as follows: School year: Year 7. Domain: Reading. View mode: Similar Schools. The chart has a grid-like layout with scattered dots. The horizontal axis is labeled “Average achievement score” and has markings ranging from 520 to 620 in increments of 20 units. The vertical axis is labeled “Number of schools” and has markings ranging from 0 to 12 in increments of 1 unit. A legend at the bottom has five types of dots, which include “Selected school,” “Substantially below 0.5 or more standard deviations below the selected school’s average,” “Below 0.2 or more, but less than 0.5 standard deviations below the selected school’s average,” “Close to within 0.2 standard deviations of the selected school’s average,” and “Above 0.2 or more, but less than 0.5 standard deviations above the selected school’s average.” The data from the chart is as follows: Selected school: (555, 2.5), labeled “Private School in N S W.” Substantially below 0.5 or more standard deviations below the selected school’s average: (540, 0.5). Below 0.2 or more, but less than 0.5 standard deviations below the selected school’s average: Nil. Close to within 0.2 standard deviations of the selected school’s average: (550, 0.5), (550, 1.5), (555, 2.5), (555, 3.5), (560, 4.5), (565, 0.5), (565, 1.5), (565, 2.5), (565, 3.5), (565, 4.5), (565, 5.5), (565, 6.5), (565, 7.5), (565, 8.5), (570, 0.5), (570, 1.5), (570, 2.5), (570, 3.5), (570, 4.5), (570, 5.5). Above 0.2 or more, but less than 0.5 standard deviations above the selected school’s average: (570, 6.5), (570, 7.5), (570, 8.5), (570, 9.5), (570, 10.5), (575, 0.5), (575, 1.5), (575, 2.5), (575, 3.5), (575, 4.5), (575, 5.5), (580, 0.5), (580, 1.5), (580, 2.5), (580, 3.5), (580, 4.5), (580, 5.5), (580, 6.5), (580, 7.5), (580, 8.5), (585, 0.5), (585, 1.5), (585, 2.5), (585, 3.5), (590, 0.5), (590, 1.5), (590, 2.5), (590, 3.5), (595, 1.5), (595, 2.5), (595, 3.5), (605, 0.5). (570, 10.5) is labeled “Private School in Q L D.” (580, 6.5) is labeled “Public School in W A.”

Screenshot of statistically similar schools display. Source: MySchool website (https://www.myschool.edu.au/)

Figure 2
A chart compares the NAPLAN scores (reading) of similar schools in 2016.The text at the top reads as follows: “‘Similar schools’” in this context are schools serving students from statistically similar backgrounds. The index of Community Socio-Educational Advantage (I C S E A) is used to group schools with students who have similar socio-educational backgrounds. For more information on I C S E A and the method used to identify statistically similar schools, visit the My School Glossary.” “This chart compares the average achievement of students from the selected schools with the average achievement of students at schools serving students from statistically similar backgrounds.” Above the chart, there are nine tabs from 2008 to 2016. The 2016 tab is currently selected. Below the tabs, fields for entering the school year, domain, and view mode with a submit button are shown. The details are as follows: School year: Year 7. Domain: Reading. View mode: Similar Schools. The chart has a grid-like layout with scattered dots. The horizontal axis is labeled “Average achievement score” and has markings ranging from 520 to 620 in increments of 20 units. The vertical axis is labeled “Number of schools” and has markings ranging from 0 to 12 in increments of 1 unit. A legend at the bottom has five types of dots, which include “Selected school,” “Substantially below 0.5 or more standard deviations below the selected school’s average,” “Below 0.2 or more, but less than 0.5 standard deviations below the selected school’s average,” “Close to within 0.2 standard deviations of the selected school’s average,” and “Above 0.2 or more, but less than 0.5 standard deviations above the selected school’s average.” The data from the chart is as follows: Selected school: (555, 2.5), labeled “Private School in N S W.” Substantially below 0.5 or more standard deviations below the selected school’s average: (540, 0.5). Below 0.2 or more, but less than 0.5 standard deviations below the selected school’s average: Nil. Close to within 0.2 standard deviations of the selected school’s average: (550, 0.5), (550, 1.5), (555, 2.5), (555, 3.5), (560, 4.5), (565, 0.5), (565, 1.5), (565, 2.5), (565, 3.5), (565, 4.5), (565, 5.5), (565, 6.5), (565, 7.5), (565, 8.5), (570, 0.5), (570, 1.5), (570, 2.5), (570, 3.5), (570, 4.5), (570, 5.5). Above 0.2 or more, but less than 0.5 standard deviations above the selected school’s average: (570, 6.5), (570, 7.5), (570, 8.5), (570, 9.5), (570, 10.5), (575, 0.5), (575, 1.5), (575, 2.5), (575, 3.5), (575, 4.5), (575, 5.5), (580, 0.5), (580, 1.5), (580, 2.5), (580, 3.5), (580, 4.5), (580, 5.5), (580, 6.5), (580, 7.5), (580, 8.5), (585, 0.5), (585, 1.5), (585, 2.5), (585, 3.5), (590, 0.5), (590, 1.5), (590, 2.5), (590, 3.5), (595, 1.5), (595, 2.5), (595, 3.5), (605, 0.5). (570, 10.5) is labeled “Private School in Q L D.” (580, 6.5) is labeled “Public School in W A.”

Screenshot of statistically similar schools display. Source: MySchool website (https://www.myschool.edu.au/)

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While comparing schools across states can provide some interesting insights, it is important to consider unique contextual factors (such as state variations in the quality of teacher preparation programs) that influence educational outcomes. A more reasonable evaluation would involve understanding and addressing contextual differences – rather than making direct comparisons without accounting for these variables. Nonetheless, the standardisation of measurement and its reduction to a single performance indicator (e.g. NAPLAN) or figure (e.g. school ranking) has created competition between schools for students, marks and resources, such as funding which is based on student enrolments (Australia Government, 2024).

This high-stakes environment has been associated with dysfunctional behavioural implications from various stakeholders and users of NAPLAN. This includes: cheating by principals and teachers to ensure “standardised” norms are met (Tomazin, 2013; Thompson, 2024); discrimination against special needs students to positively skew school's performance results (for example, asking the parents of disabled and special needs students to keep their child at home on the day of testing); teachers teaching to test and thus narrowing the curriculum (Barrett, 2014; Carter, 2017); and negative impacts on student's well-being stemming from the extreme stress of the testing process and the importance of their results (Wyn et al., 2013; Roberts and Barblett, 2024). Thus, NAPLAN has become a high-stakes test. Good performance on NAPLAN and school rankings have come to serve as key measures of a school's reputation (Wyn et al., 2013). Further, within schools, comparisons are made between teachers based on the performance of their students in NAPLAN.

During interviews, teachers characterised themselves as data entry clerks and data managers for their schools. They see their role as collators of data, with their professional judgment augmented by “objective” forms of evaluation such as assessment matrices and spreadsheets:

The tracking's more done on a spreadsheet. It's like a matrix, so you've got practically a ticking and crossing off. There will be some assessments that you have to do on paper base, you highlight where they're sitting at, then you put that data in … Then, a lot of it is collated through different events throughout the day. That's how you have the specific … I monitor those kids … I can assess where they're at. Then I can put that data in.” (Teacher, Australian Public School)

… I would after each test of quiz, or homework, piece of homework that they've got marked off, within that day I was expected to update the spreadsheet. The good thing about the spreadsheet, you could from there, the spreadsheet automatically calculated the students average and the grade. Also, would let you know what the ranking of the student was in your class but also in the year level, which is good when you're talking to parents who think their child deserves more opportunities or deserves to be promoted into the extension group. You can say their ranking doesn't say that they should. (Teacher, Australian Private School)

As such, schools are changing their performance management and decision-making processes from one that was knowledge-driven and based on a teacher’s experience of their students (“I can tell that that's not their ability”) to one that is data-driven (“the spreadsheet automatically calculated the students average and the grade”).

Moreover, student rankings are not just formulated individually or in relation to classmates. Comparisons are made nationally with all students at their level. Armed with these accounting numbers and average student calculations, teachers and the school can better target resources for students who are performing below average to improve overall school performance. Improving overall school performance is essential to building a school's reputation and its ability to attract more students and, hence, more funding (Perry, 2025; Preston, 2023) and other resources (such as additional teachers and support staff). Such intimate accountings are also used to create models of potential future performance, which guide the school, teachers and students in their everyday choices with a view to obtaining the best possible results in further testing (Merrett, 2015). As explained by a school principal:

In our school we have a whole range of data sets, NAPLAN results to everyday testing literacy and numeracy that happens. We have a data analyst team as well … They will analyse data, look at areas where there may be deficiencies. They'll come to me as the principal, and they'll talk about where the deficiencies are, what process we need to put in place to make sure we're managing those deficiencies from financial resourcing [perspective] … Obviously, when the NAPLAN data comes out in November there's a huge analysation process that takes place. Plans are then put in place forward of that data. If we're looking at 2016 you put plans in place with 2017 to make sure we're fixing up the deficiencies that we see in that data. (Principal, Australian Public School)

Like Corvellec et al.’s (2018) invoicing inscriptions acting at a distance to govern everyday householders' waste practices, we observed schools creating their own accounting inscriptions that are collated and organised through student and parent portals. Schools implemented these portals to improve communication and offer both students and parents easy access to individualised information relating to how a student is performing at school. Figure 3 provides an example of a parent portal covering information regarding a student's timetable, resources, attendance, well-being, reporting, assessments and school records – key concerns relating to a student's NAPLAN results.

Figure 3
A colour-coded data table comparing school performance.The screen is from a desktop, with a visible browser window. A red top banner labeled “Parent Portal” is partially visible. At the top, the page title reads “Attendance” with a dropdown arrow. Below this title, there are five navigation tabs with icons which include “overview,” “Class Attendance,” “Unexplained Absences,” “Explained Absences,” and “Exempt Absences.” Below the navigation tabs, the section header is titled “Attendance Overview” with descriptive text below: “The attendance overview shows a ‘heatmap’ which outlines all school absences, both explained and unexplained. Hovering your mouse over the specific day will show full details of the times and…” Heatmap Structure (Terms 1 to 4). The visual heatmap is split into four columns, each representing a school term (Term 1 through Term 4). Each term contains a grid of blocks. Rows represent weeks (W 1 to W 11). Columns represent weekdays (Monday to Friday). Each small cell in the grid corresponds to one day and is color-coded as follows: Green: Present. Orange: Explained absence. Gray: Exempt absence. White or blank: Likely unexplained absence, future dates, or missing data. On the right, a compact summary shows attendance percentages: Term 1: 93.9 percent. Term 2: 100 percent. Term 3: 100 percent. Term 4: No percentage shown. Overall Attendance: 97.5 percent.

Screenshot of a school portal. Source: Photograph taken by lead authors

Figure 3
A colour-coded data table comparing school performance.The screen is from a desktop, with a visible browser window. A red top banner labeled “Parent Portal” is partially visible. At the top, the page title reads “Attendance” with a dropdown arrow. Below this title, there are five navigation tabs with icons which include “overview,” “Class Attendance,” “Unexplained Absences,” “Explained Absences,” and “Exempt Absences.” Below the navigation tabs, the section header is titled “Attendance Overview” with descriptive text below: “The attendance overview shows a ‘heatmap’ which outlines all school absences, both explained and unexplained. Hovering your mouse over the specific day will show full details of the times and…” Heatmap Structure (Terms 1 to 4). The visual heatmap is split into four columns, each representing a school term (Term 1 through Term 4). Each term contains a grid of blocks. Rows represent weeks (W 1 to W 11). Columns represent weekdays (Monday to Friday). Each small cell in the grid corresponds to one day and is color-coded as follows: Green: Present. Orange: Explained absence. Gray: Exempt absence. White or blank: Likely unexplained absence, future dates, or missing data. On the right, a compact summary shows attendance percentages: Term 1: 93.9 percent. Term 2: 100 percent. Term 3: 100 percent. Term 4: No percentage shown. Overall Attendance: 97.5 percent.

Screenshot of a school portal. Source: Photograph taken by lead authors

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It is interesting to note that most of the information within this school's portal relates back to the Key Performance Measures (KPM), student attendance, as outlined in the policy document, Measurement Framework for Schooling in Australia (ACARA, 2015). Other matters of concern being tracked in these portals, including student well-being, also relate to exam results. For example, on 24th August 2016, the well-being section of the school portal viewed as part of this research contained the statement, “Students are not working to their full capacity and teacher is concerned about their performance in the upcoming Preliminary Exam and their results will reflect their effort.” Therefore, students' academic performance with respect to assessments, such as NAPLAN, assume precedence, drawing schools, teachers, students and parents into a more intimate relationship with the key metrics established and monitored by ACARA.

Thus, monitoring student performance is not only the school and teachers’ jobs but also extends to parents. Parents are expected to log into their assigned parent portal and acknowledge, track and occasionally provide explanations for their children’s performance, behaviour or absence from school. A parent explained:

I can see their homework, what homework they get for each class. I can see it. I also have the opportunity to say, “Yes, they've done this,” so that they [teachers] know that I know that they've done it … I can actually see if my daughter's missed a period, because it says she was absent for that period. And I say to her, “Where were you? Why didn't you go to that class?” And she would say, “Mum, we had a dance incursion … We had that for period one and two, so that means I was absent from my usual classes,” so I can see all of that. (Parent, Australian Private School)

While parents previously focused on how their child was doing in school via traditional forms of paper report cards, these forms of intimate, real-time and digitally mediated accounting requires them to participate in the school's day-to-day accountability practices. We now turn to the overflows of these everyday educational accountabilities, focusing on the types accounting intimacy enrolling parents.

4.2.2 Parents

It was observed that it is not only schools collecting and analysing data to inform their decisions and “intimate action” (Asdal, 2011, p. 6). Parents also collect their own data, analysing spreadsheets and rubrics of data – either self-created or requested from the school – to assess the performance of schools and/or their children. For example, a parent created the spreadsheet in Figure 4. This spreadsheet helped her analyse the five schools she was considering for her children. She explained her reasons for creating the spreadsheet:

Figure 4
A color-coded data table comparing student performance.The table consists of 6 columns and 37 rows. The column headers in row 1 are no heading, S I P S, G E P S, W P S, P L C, R slash wood. The data entries in the table are as follows: Row 2: Column 1: Total enrollments; S I P S: 367; G E P S: 323; W P S: 124 (green); P L C: 2156; R slash wood: 1043. Row 3: Column 1: Girls; S I P S: 210; G E P S: 155; W P S: 49 (green); P L C: 2156; R slash wood: 1043. Row 4: Column 1: Boys; S I P S: 157; G E P S: 168; W P S: 75 (green); P L C: Blank; R slash wood: Blank. Row 5: Column 1: L B O T E; S I P S: 20 percent; G E P S: 32 percent; W P S: 8 percent; P L C: Blank; R slash wood: Blank. Row 6: Column 1: Teaching staff; S I P S: 18; G E P S: 15; W P S: 14 (green); P L C: 220; R slash wood: 128. Row 7: Column 1: Year 3; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 8: Column 1: Reading; S I P S: 482 (orange); G E P S: 485 (orange); W P S: 432; P L C: 496 (green); R slash wood: 473. Row 9: Column 1: Persuasive writing; S I P S: 485 (green); G E P S: 443; W P S: 469 (orange); P L C: 486 (green); R slash wood: 477 (orange). Row 10: Column 1: Spelling; S I P S: 460 (orange); G E P S: 455; W P S: 459 (orange); P L C: 488 (green); R slash wood: 463 (orange). Row 11: Column 1: Grammar and punctuation; S I P S: 487 (orange); G E P S: 473; W P S: 548 (green); P L C: 527 (green); R slash wood: 491 (orange). Row 12: Column 1: Numeracy; S I P S: 462 (orange); G E P S: 448 (orange); W P S: 482 (green); P L C: 468 (green); R slash wood: 433. Row 13: Column 1: Year 5; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 14: Column 1: Reading; S I P S: 531; G E P S: 556; W P S: 540 (green); P L C: 574 (green); R slash wood: 567 (orange). Row 15: Column 1: Persuasive writing; S I P S: 495 (orange); G E P S: 516; W P S: 562 (green); P L C: 555 (green); R slash wood: 535 (orange). Row 15: Column 1: Spelling; S I P S: 534; G E P S: 557 (orange); W P S: 559 (green); P L C: 563 (green); R slash wood: 549. Row 16: Column 1: Grammar and punctuation; S I P S: 539; G E P S: 559; W P S: 604 (green); P L C: 581 (green); R slash wood: 574 (orange). Row 17: Column 1: Numeracy; S I P S: 551 (orange); G E P S: 575 (orange); W P S: 565 (green); P L C: 565 (green); R slash wood: 521. Row 18: Column 1: Year 7; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 19: Column 1: Reading; S I P S: 531; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 20: Column 1: Persuasive writing; S I P S: 495 (orange); G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 21: Column 1: Spelling; S I P S: 534; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 22: Column 1: Grammar and punctuation; S I P S: 539; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 23: Column 1: Numeracy; S I P S: 551 (orange); G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 24: Column 1: Year 9; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 25: Column 1: Reading; S I P S: 531; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 26: Column 1: Persuasive writing; S I P S: 495 (orange); G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 27: Column 1: Spelling; S I P S: 534; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 28: Column 1: Grammar and punctuation; S I P S: 539; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 29: Column 1: Numeracy; S I P S: 551 (orange); G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 30: Column 1: Blank; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 31: Column 1: Music; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 32: Column 1: L O T E; S I P S: Mandarin, Italian; G E P S: french; W P S: Japanese; P L C: Blank; R slash wood: Blank. Row 33: Column 1: Drama; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 34: Column 1: Debating; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 35: Column 1: Positives; S I P S: 1. S I P S green team, 2. 2 streams per year, 4. friends going here; G E P S: 1. boys over girls, 2. french, 3. robotics, years 2 to 6, 4. 2 streams per year, 5. ease in terms of geography, 6. recommendations, 7. slightly smaller; W P S: 1. boys over girls, 2. music program and choice of instruments in after school lessons, 3. ratio of teacher to a student care, 4. 2 streams per year; P L C: 1. Girls able to be separated or find their own peer group and interests, 2. Enough activities at multiple levels to allow for different levels of accomplishment; R slash wood: 1. Past oral care emphasis, 2. Location (rail), 3. Positive psychology. Row 36: Column 1: Ask about; S I P S: 1. language; G E P S: 1. language; W P S: 1. why year 3 Na plan less positive, especially reading question mark, 2. How do you manage boys versus girls question mark, Are girls empowered question mark, 3. I think only 1 stream per year question mark; P L C: Blank; R slash wood: 1. Why Na plan results so low question mark. Row 37: Column 1: Cons or concerns; S I P S: Blank; G E P S: Blank; W P S: Distance Cost; P L C: 1. Open learning spaces, 2. Probably overwhelming for girls, 3. Not convinced they can really cater to the individual; R slash wood: Cost Girls only.

School pros and cons spreadsheet created by a parent. Source: Provided by research participant during interview (de-identified)

Figure 4
A color-coded data table comparing student performance.The table consists of 6 columns and 37 rows. The column headers in row 1 are no heading, S I P S, G E P S, W P S, P L C, R slash wood. The data entries in the table are as follows: Row 2: Column 1: Total enrollments; S I P S: 367; G E P S: 323; W P S: 124 (green); P L C: 2156; R slash wood: 1043. Row 3: Column 1: Girls; S I P S: 210; G E P S: 155; W P S: 49 (green); P L C: 2156; R slash wood: 1043. Row 4: Column 1: Boys; S I P S: 157; G E P S: 168; W P S: 75 (green); P L C: Blank; R slash wood: Blank. Row 5: Column 1: L B O T E; S I P S: 20 percent; G E P S: 32 percent; W P S: 8 percent; P L C: Blank; R slash wood: Blank. Row 6: Column 1: Teaching staff; S I P S: 18; G E P S: 15; W P S: 14 (green); P L C: 220; R slash wood: 128. Row 7: Column 1: Year 3; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 8: Column 1: Reading; S I P S: 482 (orange); G E P S: 485 (orange); W P S: 432; P L C: 496 (green); R slash wood: 473. Row 9: Column 1: Persuasive writing; S I P S: 485 (green); G E P S: 443; W P S: 469 (orange); P L C: 486 (green); R slash wood: 477 (orange). Row 10: Column 1: Spelling; S I P S: 460 (orange); G E P S: 455; W P S: 459 (orange); P L C: 488 (green); R slash wood: 463 (orange). Row 11: Column 1: Grammar and punctuation; S I P S: 487 (orange); G E P S: 473; W P S: 548 (green); P L C: 527 (green); R slash wood: 491 (orange). Row 12: Column 1: Numeracy; S I P S: 462 (orange); G E P S: 448 (orange); W P S: 482 (green); P L C: 468 (green); R slash wood: 433. Row 13: Column 1: Year 5; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 14: Column 1: Reading; S I P S: 531; G E P S: 556; W P S: 540 (green); P L C: 574 (green); R slash wood: 567 (orange). Row 15: Column 1: Persuasive writing; S I P S: 495 (orange); G E P S: 516; W P S: 562 (green); P L C: 555 (green); R slash wood: 535 (orange). Row 15: Column 1: Spelling; S I P S: 534; G E P S: 557 (orange); W P S: 559 (green); P L C: 563 (green); R slash wood: 549. Row 16: Column 1: Grammar and punctuation; S I P S: 539; G E P S: 559; W P S: 604 (green); P L C: 581 (green); R slash wood: 574 (orange). Row 17: Column 1: Numeracy; S I P S: 551 (orange); G E P S: 575 (orange); W P S: 565 (green); P L C: 565 (green); R slash wood: 521. Row 18: Column 1: Year 7; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 19: Column 1: Reading; S I P S: 531; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 20: Column 1: Persuasive writing; S I P S: 495 (orange); G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 21: Column 1: Spelling; S I P S: 534; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 22: Column 1: Grammar and punctuation; S I P S: 539; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 23: Column 1: Numeracy; S I P S: 551 (orange); G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 24: Column 1: Year 9; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 25: Column 1: Reading; S I P S: 531; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 26: Column 1: Persuasive writing; S I P S: 495 (orange); G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 27: Column 1: Spelling; S I P S: 534; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 28: Column 1: Grammar and punctuation; S I P S: 539; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 29: Column 1: Numeracy; S I P S: 551 (orange); G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 30: Column 1: Blank; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 31: Column 1: Music; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 32: Column 1: L O T E; S I P S: Mandarin, Italian; G E P S: french; W P S: Japanese; P L C: Blank; R slash wood: Blank. Row 33: Column 1: Drama; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 34: Column 1: Debating; S I P S: Blank; G E P S: Blank; W P S: Blank; P L C: Blank; R slash wood: Blank. Row 35: Column 1: Positives; S I P S: 1. S I P S green team, 2. 2 streams per year, 4. friends going here; G E P S: 1. boys over girls, 2. french, 3. robotics, years 2 to 6, 4. 2 streams per year, 5. ease in terms of geography, 6. recommendations, 7. slightly smaller; W P S: 1. boys over girls, 2. music program and choice of instruments in after school lessons, 3. ratio of teacher to a student care, 4. 2 streams per year; P L C: 1. Girls able to be separated or find their own peer group and interests, 2. Enough activities at multiple levels to allow for different levels of accomplishment; R slash wood: 1. Past oral care emphasis, 2. Location (rail), 3. Positive psychology. Row 36: Column 1: Ask about; S I P S: 1. language; G E P S: 1. language; W P S: 1. why year 3 Na plan less positive, especially reading question mark, 2. How do you manage boys versus girls question mark, Are girls empowered question mark, 3. I think only 1 stream per year question mark; P L C: Blank; R slash wood: 1. Why Na plan results so low question mark. Row 37: Column 1: Cons or concerns; S I P S: Blank; G E P S: Blank; W P S: Distance Cost; P L C: 1. Open learning spaces, 2. Probably overwhelming for girls, 3. Not convinced they can really cater to the individual; R slash wood: Cost Girls only.

School pros and cons spreadsheet created by a parent. Source: Provided by research participant during interview (de-identified)

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In terms of the spreadsheet, the way that I coloured it was green for PLC because they had the higher NAPLAN results and then orange for the ones that were next and then a couple of the other ones were just blank. When you're using NAPLAN, I think you can compare similar schools, but if there's a difference in terms of the socio-economic, then you can't compare them, so that's why I started with the spreadsheet to just enable my own comparisons because I was looking at public and at private schools. (Parent 9, Australian Public School)

Regarding Figure 4, the parent collected data from the government MySchool website, which provided access to the NAPLAN scores for schools of interest. However, she also self-collected other numbers and qualitative information that was relevant to her decision making. This included the ratio of teachers to students, the number of streams in a year, types of extracurricular activities, pastoral care, costs and types of learning spaces at the school. Here, the parent was not just a passive consumer of information but also actively analysed and produced her own calculative framework to compare schools of interest – although her framework was heavily reliant on the same imposed performance metric (that is, NAPLAN scores) defining school accountability.

Parents' calculative frameworks, such as the above spreadsheet, are driven by neoliberal market forces and logics. Correspondingly, parents are consumers calculating their own cost/benefit/value-add (Groff et al., 2010), exercising choice when allocating “given scarce resources to this end [school] rather than another” (Foucault, 2008, p. 223). Similarly, such accounting calculations, concerning the costs of private schooling and the overall value of education provided, were raised during interviews with other parents. For example, a parent who had experienced both private school and public education stated:

The curriculum, at the public school compared to the private [Catholic] school, was exactly the same. There was no difference in curriculum … If you're paying just to get religion, well, why are we really paying for it, so that was one of the drivers, the cost … (Parent, Australian Public School)

Parents also use publicly available and intimate details of student performance contained in NAPLAN scores to make key decisions regarding school choice – and to persuade proximate others, such as spouses, to accept preferred choices. Accordingly, many referred to MySchool numbers and calculations configuring intimate spaces via media debate about school rankings and ratings. The media regularly compiles, publishes and discusses hierarchical rankings of schools based on NAPLAN test results and other numbers (such as Higher School Certificate (HSC) matriculation results), consolidating and communicating information about schools in the Australian education sector. For example, a parent shared how she used the intimate accounting information from the MySchool website to persuade her spouse to enrol their daughters in a public school, rather than a private one aligned with their religious faith:

So there, I think my decision, I feel like, if I can convince my husband … I wanted them to be at a school that was in, say, the top 50 or 60 in New South Wales … It was their ranking in terms of their MySchool website and their HSC results. If they were sort of 200 or 300, I probably would've gone, “Oh, maybe not,” for the public system, for the public school. It did influence our decision in the end, yes. We sort of thought, Well, we're paying to send them to a Catholic school. Their academic results aren't as good as the public school, so why do we want to pay? And they're going to a better school … The public school that my girls went to ranked 60 spots ahead of all the private girls' schools. (Parent, Australian Public School)

These quotes highlight that, within the neoliberal context of the Australian education sector, everyday decision making – including the sacred (Foucault, 2008, p. 244) – is (re)thought along economic lines. Accounting and its calculative practices act on and interpenetrate every inch of the “market” (Lawrence and Sharma, 2002), resulting in the enrolment of many other actors not traditionally conceived as having interests in the school sector. It is to these other actors that we now turn our attention.

4.2.3 Other actors

Our analysis found a number of “surprising” actors participating in the intimate accountings of school education in Australia – from newspapers publishing league tables of schools using the information available on the MySchool website to real estate agents using MySchool and media-created school rankings/ratings to calculate the value of housing (Bleby, 2017; Sproul-Mellis, 2024). For example, News Corp Australia, one of Australia's largest media outlets used by over 17 million Australians, produces a yearly “Bang for Buck” real estate feature. This feature analyses the NAPLAN results of school catchment areas to provide detailed accounts and analyses of property prices in these areas. For example, as reported in the media:

News Corp’s “bang for buck” real estate feature has revealed how property prices and school catchments overlap. For example, NAPLAN high-performer Hornsby North Public School’s intake area has a median house price nearly $200,000 higher than neighbouring Hornsby Heights', while in the Sutherland Shire, the intake for Sutherland North Public School garners slightly higher house prices than lower-ranked neighbour Jannali Public. (Sproul-Mellis, 2024)

According to News Corp, their “Bang for your Buck” research is based on an accounting formula that “uses the latest NAPLAN results, PropTrack's median house price values and school catchment mapping to deliver insight into parents looking to get the best value for money” (Bueti, 2024). Heatmap visualisations, reducing intimate school data to a selected metric (in this case, property values), provide consumers, such as parents, with an effective and efficient way to easily compare data values when presented numerically in a spreadsheet (Hofer et al., 2023). An example is provided in Figure 5.

Figure 5
A news article shows the map of New South Wales.The headline of the article reads “Suburbs with affordable housing in school zones with top NAPLAN results.” The subtext below the headline reads as follows: “Below are the top suburbs for families across Australia, picked through NewsCorp’s 'Bank for your Buck’ research based on the criteria mentioned above, scored against NAPLAN results of the close-by schools.” The map of New South Wales shows areas such as North Sydney, Sydney C B D, Mosman, Vaucluse, Watsons Bay, Hunters Hill, Balmain, Redfern, Dover Heights, Bondi Beach, and surrounding suburbs. Suburbs are shaded in various intensities of blue, which represent the strength of nearby schools’ NAPLAN performance relative to affordability. There are zoom-in and zoom-out buttons on the top left of the map. At the bottom, a caption reads: “See which public primary and secondary schools are shaping the N S W property market due to their impressive NAPLAN results.”

Screenshot of NewsCorp’s Bang for your Buck real estate feature. Source: News Corp Australia Network (https://www.news.com.au/)

Figure 5
A news article shows the map of New South Wales.The headline of the article reads “Suburbs with affordable housing in school zones with top NAPLAN results.” The subtext below the headline reads as follows: “Below are the top suburbs for families across Australia, picked through NewsCorp’s 'Bank for your Buck’ research based on the criteria mentioned above, scored against NAPLAN results of the close-by schools.” The map of New South Wales shows areas such as North Sydney, Sydney C B D, Mosman, Vaucluse, Watsons Bay, Hunters Hill, Balmain, Redfern, Dover Heights, Bondi Beach, and surrounding suburbs. Suburbs are shaded in various intensities of blue, which represent the strength of nearby schools’ NAPLAN performance relative to affordability. There are zoom-in and zoom-out buttons on the top left of the map. At the bottom, a caption reads: “See which public primary and secondary schools are shaping the N S W property market due to their impressive NAPLAN results.”

Screenshot of NewsCorp’s Bang for your Buck real estate feature. Source: News Corp Australia Network (https://www.news.com.au/)

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The media has reported numerous cases of parents strategically relocating closer to their preferred “top” public schools (Smith, 2014), leading to abnormal increases in property values across Australia. Real estate in high-demand school zones now commands significant premiums (Gothe-snape, 2014; Sproul-Mellis, 2024). Moreover, proximity to good schools has become an entrenched part of real estate marketing strategies.

Other commercial actors and interests have also taken advantage of this publicly and easily accessible educational information, developing new lines of business. For example, a whole suite of NAPLAN study materials has emerged. Further, tutoring to improve NAPLAN and other test results is now a billion-dollar industry in Australia (McDougall, 2014; Chapman, 2020).

Interviews with parents revealed that they not only seek evaluations of their children’s performance but also actively seek to improve their children’s performance by purchasing extra assessment practice workbooks and tests, as well as hiring NAPLAN tutors. This trend persists despite criticism that MySchool is a “web of misinformation” (Zyngier, 2010), with studies revealing that NAPLAN is based on flawed and incomplete data, failing to provide meaningful analysis or accurately measure the performance of individual schools (Zyngier, 2010; Wyn et al., 2013). Correspondingly, the extant literature reminds us that the persuasiveness of accounting numbers does not arise from its representational fidelity, but rather from assertions regarding its impartiality and the robustness of the procedures inscribing reality (Goretzki et al., 2018; Miller and Rose, 2008; Porter, 1994). It is this process of inscription that has enabled both action from a distance and on distance via intimate and relationally constructed spaces. The next section discusses our findings.

Based on our study of governance in the Australian education sector, we find a series of cascading translations of governmentality, involving global, national, state, organisational and individual actors, influencing and influenced by one another and connected via calculative practices. As was illustrated in the case study, Australia's goal of ranking in the Top 5 of the OECD’s PISA ranking by 2025 led to an overflowing of calculative infrastructures and governmentality, interconnecting global actors with everyday objects and relations. Global actors, such as the OECD, generate large-scale universal data (like the PISA ranking) facilitating comparisons at the national level. National policymakers use these datasets to justify reforms, such as the MySchool website and establishment of ACARA in Australia. In turn, global actors collaborate with national actors, including governments and policy institutions (like ACARA), to standardise and quantify education through the creation of calculative infrastructures and the implementation of neoliberal policies focused on standardisation.

National actors, such as the Australian federal government, have created a range of programmes and technologies of governance emphasising a need for large-scale quantification grounded in neoliberal arguments – that is, universal competition depends on universal calculation and comparison. As a result, government policies have established standardised outcomes, made visible through standardised accounting datasets (such as NAPLAN), functioning as mechanisms of accountability. Socially constructed categories, like ICSEA, facilitate comparisons across populations and help justify large-scale accounting inscriptions, such as the MySchool website.

These forms of programmes and technologies of governance are further translated by state actors, as seen in the development of policies and tools by Australian state governments (such as Queensland) and their agencies. These policies set quantified targets, benchmarks and strategic plans, often using the same categories as ICSEA. Targets are typically linked to funding (Aliabadi et al., 2021) to ensure that school actors focus on and, crucially, meet standardised outcomes. Additionally, other state actors, such as newspapers, produce school comparison tools (like rankings based on testing outcomes) to hold national, state and school actors accountable for Australia's educational performance. Such media coverage and comparison tools usually rely on the national and state accounting datasets, drawing from established educational and social categories, further legitimising and intensifying the emphasis on educational measurement and evaluation based on standardised outcomes.

As a result, organisational actors, such as principals in the MySchool case study, develop local school policies and accountability infrastructures, including parent and student portals and data-driven curricula and pedagogy, to achieve standardised outcomes. This requires teachers and students to meet the standards set within these policies and infrastructures, engaging in a continuous process of calculative accountability – recording, analysing and justifying standardised outcomes.

This, in turn, enrols individuals, such as parents, using accountability tools (like parent portals) to monitor their child's performance (for example, in NAPLAN tests). In addition to monitoring the performance of others, actors also create and use various calculative inscriptions, such as spreadsheets, to “compare and calculate the costliness of his or her actions, and that of others” (Kurunmaki and Miller, 2006, p. 87). This, in turn, assists informed decisions about the future (Where shall I send my child to school? What is the value of a private school education in my child's future?). As demonstrated in our case study, these accounting inscriptions are often driven by algorithms, like media school comparison tools, relying on the same national and state accounting datasets and socially constructed categories engineered by governments.

We summarise these cascading translations of governmentality in Figure 6.

Figure 6
A flowchart shows 5 levels of actors influencing education: global, national, state, organisational (school), and individual.The hierarchical flowchart represents different levels of actors involved in educational assessment and accountability systems. The flow descends from global to individual levels, with curved arrows on both sides indicating interaction and feedback between layers. Levels of Actors: Level 1: Global Actor; For example: O E C D’s P I S A, International P I S A Ranking. Level 2: National Actor; For example: A C A R A; MySchool Website. Level 3: State Actor; For example: N S W Literacy and Numeracy Strategic Plans; Media Ranking. Level 4: Organisational (School) Actor; For example: Creation of School Management Tools; Facebook Rating. Level 5: Individual Actor; For example: Creation of Self-tracking Devices (Excel spreadsheets created by Parents; Goal Sheets created by Students).

Cascading translations of governmentality in the Australian Education Sector. Source: Diagram created by authors, each arrow represents chains of calculations effected and affected by various actors in the Australian Education Sector

Figure 6
A flowchart shows 5 levels of actors influencing education: global, national, state, organisational (school), and individual.The hierarchical flowchart represents different levels of actors involved in educational assessment and accountability systems. The flow descends from global to individual levels, with curved arrows on both sides indicating interaction and feedback between layers. Levels of Actors: Level 1: Global Actor; For example: O E C D’s P I S A, International P I S A Ranking. Level 2: National Actor; For example: A C A R A; MySchool Website. Level 3: State Actor; For example: N S W Literacy and Numeracy Strategic Plans; Media Ranking. Level 4: Organisational (School) Actor; For example: Creation of School Management Tools; Facebook Rating. Level 5: Individual Actor; For example: Creation of Self-tracking Devices (Excel spreadsheets created by Parents; Goal Sheets created by Students).

Cascading translations of governmentality in the Australian Education Sector. Source: Diagram created by authors, each arrow represents chains of calculations effected and affected by various actors in the Australian Education Sector

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As shown in Figure 6, governmentality is enacted through closely connected chains of coupling, wherein each actor primarily governs the other by managing the possibilities of control. The former translates the competence of the latter, facilitating and imposing control along chains of calculations and translations. It is through this chain of calculative governmentality that actors become intimately linked by a form of mutual (govern) mentality.

These cascading translations of governmentality sustain “accounting intimacy,” a term coined by Kristin Asdal (2011, p. 6). “Accounting intimacy” is characterised by accounting and calculative practices translating distant, abstract and disembodied centres of calculation into more dispersed, situationally meaningful, local and embodied calculable spaces, drawing policy into everyday practices. Thus, accountability becomes highly intimate and relational – acting on distance. Thus, it becomes possible for educators, parents, students or even a real estate agents and tutors to inform Australia’s education revolution.

In this context, accounting and calculations do not simply represent or reference existing states of affairs (Mennicken and Miller, 2012; Robson, 1992). Rather, they influence and transform the very object they are intending to represent, actively producing and mediating new relations between actors, and creating new conditions and possibilities for action. As demonstrated in our case study, accounting numbers and calculations act on distances, enable previously distant groups of actors to form intimate relationships with organisations and other entities, exert pressure on them and hold them accountable.

Accordingly, accounting is not only acting at a distance but also shaping those distances (Corvellec et al., 2018) through practices of accounting intimacy. It is through these technologies of government – whether created by the state (e.g. the MySchool website), schools (e.g. student and parent portals) or even third-party websites (e.g. media ranking tools) – that the state and its calculative inscriptions infiltrate the intimate spaces of schools configuring relations between not only teachers and students but also the intimate spaces occupied by parents and local communities. Schools and their accountability tools enter these spaces creating dynamic feedback loops (refer to Figure 6), whereby the intimate spaces of the school, home, local communities and broader network influence each other.

Overall, this paper contributes to the literature in four main ways. First, our paper provides analytical insight into how a calculative infrastructure has been made to “fit” and work in practice (Miller, 2014). As a result of studying educational governance in Australia, we offer an analytical notion framing this fit in terms of cascading translations of governmentality. Extant studies of governmentality have tended to view its operations as a means for entities to govern the bodies of their populace (Ahrens et al., 2020; Neu, 2000; McKinlay and Pezet, 2010), providing a top-down, state-initiated policy agenda (Miller, 1991). In comparison, we conceptualise governance as a cascade of multiple and interconnected translations, connecting multiple actors. These actors are global (e.g. OECD), national (e.g. ACARA), state (e.g. NSW Literacy and Numeracy Strategic Plans), school-based (e.g. principals, teachers) and individual (e.g. parents, students). Moreover, they are held together by an array of calculative processes (e.g. the PISA ranking of the OECD, the MySchool website of the Australian Federal Government, matriculation exam results of the states, such as the HSC in NSW, the rankings of students within schools and the spreadsheets constructed by families making educational choices). In contrast to extant research, our study shows that school governance is far more encompassing and interconnected than actions taken by school boards (Unda et al., 2023), the policy formulation process (Miller, 1991) or the operation of institutions (Ahrens et al., 2020; McKinlay and Pezet, 2010).

Second, our paper augments studies that have examined the relations between accounting, action and distance (Corvellec et al., 2018; Quattrone and Hopper, 2005; Robson, 1992). We argue that (Australian educational) governance involves both action from a distance and acting on distance. Our case illustrates that acting on distances via forms of what Asdal (2011) described as “intimate accounting” is as equally important as the establishment and operation of macro actors (such as the OECD and ACARA), policies (the Australian Federal Government's Education Revolution) and infrastructures (such as MySchool) enabling action at a distance (Miller, 1991; Robson, 1992). It is intimate accounting that translates abstract, distant and disembodied forms of action at a distance into situationally meaningful, localised and embodied practices: the “nitty-gritty” of everyday, mundane calculations constitutes relations (between schools and ACARA, parents and MySchool, teachers and students, real estate agents and communities, for example) that act on distances and make governance both workable and possible.

Third, by empirically demonstrating how cascading translations of governmentality are connected to and mutually constituted by accounting intimacy, we also show how these forms of intimacies create new intimacies with unexpected actors (such as real estate actors), capable of significantly impacting decision making both within and outside the education domain. While previous accounting studies have explored the link between macro-level government policies and accounting inscriptions in traditional organisational domains (Grossi et al., 2020; Miller, 1991), our paper further highlights the spillovers and unintended effects of accounting calculations in the intimate and mundane spaces of everyday life. We have highlighted how the measurement of school performance via MySchool has affected decisions as to where families live, real estate prices in different school catchment areas, the growing pressure on students to perform on a narrow range of tests, family discussions about the worth of paying for “religion” in the context of schooling, unparalleled media scrutiny of poorly performing but often severely under resourced schools, parents removing children from schools in response to rankings, the growing administrative burden placed on classroom teachers, schools employing dedicated analysts to manage reporting requirements and make recommendations for improving future testing outcomes, and the growth of private tutoring as an industry, for example. The calculative complex embedded in Australian educational governance is far from “innocent” in its effects, reshaping manifold aspects of our society.

Fourth, our study contributes to the small corpus of accounting research providing empirical insights into educational governance (Edwards et al., 1999; Neu, 2006), particularly in the context of schools (Cutler and Waine, 2004; Edwards et al., 2000; Groff et al., 2010; Levacic, 1990; Rubin, 2004; Unda et al., 2023). Without such insights, there is no evidence-based platform for formulating the practical and policy implications of educational governance and its associated calculative practices and inscriptions. As such, our paper is a rudimentary evidentiary building block in the domain of school education. Moreover, this is an area that is fecund with research prospect and potential impact. For example, spending on education and the allocation of funding to schools is a significant economic activity, consuming a material proportion of the Australian national budget (Australia Government, 2024) and attracting significant debate as to the adequacy and equity of funding allocations to schools (Perry, 2025; Preston, 2023). We hope that our study encourages others to undertake accounting research in this and other neglected areas related to educational governance.

Further, there are three main practical implications stemming from our study, especially for policymakers, educators and researchers interested in understanding the interpenetration of governance, accounting and everyday practices. First, our study encourages a shift in how we understand governmentality in education and other knowledge-intensive public organisation contexts, such as healthcare (Grossi et al., 2020). Highlighting the cascading translations of governance and the role of intimate accounting in making governance work, policymakers should consider how initiatives will be interpreted and enacted locally, ensuring that a range of local actors are not only seen as subjects of policy but also as active participants capable of shaping the performance outcomes of proposed governance practices. Further, policymakers are also advised to contemplate and heed the unintended consequences emanating from governance work.

Second, by illustrating how intimate accounting practices reconstitute lived experiences, our study suggests that accountability should extend to consequent personal and relational impacts (Quattrone, 2009) and spillovers. Stakeholders in education, including school administrators and policymakers, should be encouraged to rethink the design of accountability mechanisms to minimise unintended consequences, such as increased pressure on students from testing or the overburdening of parents (financially and mentally). It is argued that more attention needs to be paid to the ways in which these systems impact the emotional and relational aspects of actors implicated in the practices of educational governance.

Third, with respect to public actors such as media commentators, real estate agents and other external stakeholders (including tutoring businesses), our paper suggests that their involvement in education through ranking and comparison tools has direct consequences for educational governance, particularly in conjunction with the everyday relations constituting family life. Such external actors can use this insight to reflect on the social responsibility of their roles in shaping public perceptions of schools and educational outcomes, including how these outcomes are viewed and calculated (valued) by others. Our research encourages educators and school leaders to engage proactively with the broader community to understand and reconfigure their role within the network of relations ultimately sustaining them (via funding, access to students, reputational capital and so on) (Revellino and Mouritsen, 2015). For example, can governance practices be used to encourage the leaders of private schools richly endowed with sporting and cultural facilities to (re)evaluate their role in local communities lacking such resources?

The findings and implications of our study should also be considered in the light of their limitations. Our study has focused solely on the Australian education sector, which may not fully reflect other neoliberal public sector systems shaped by different political and economic contexts. Also, the use of snowball sampling may have introduced selection bias, as initial interviewees may refer others with similar views and experiences. Thus, some perspectives may be underrepresented. Our study is also limited by the type of data collected, relying heavily on calculative inscriptions (for example, MySchool and related systems) and their impact on governance. This may overshadow other influential factors in the education sector. In a bid to counter these limitations, we employed multiple data collection methods (document review, media analysis and interviews) and data triangulation. We believe that the constant comparative method (Glaser and Strauss, 1967) used in our data analysis has strengthened the robustness of our findings (Silverman, 2010).

Nonetheless, the limitations outlined above present opportunities for future research. By broadening the scope of research, linking policies to everyday practices, researchers in the field of accounting and governance can build on this study by exploring the spillover effects of accounting practices in personal and intimate spaces by looking beyond the education sector (e.g. healthcare, sustainability, infrastructure provision). Conducting cross-national studies would allow for a broader understanding of how neoliberal governance and accounting practices manifest, selecting countries with different governance models or economic conditions (developing versus developed), enabling the identification of commonalities and differences in governance, accounting and accountability. This could lead to a more comprehensive understanding of how accounting and performance measurement shape social relationships, influencing not just organisational behaviour but also individual lives in significant and intimate ways. Finally, this paper acknowledges that accounting intimacy is not without resistance. Future research could explore the resistance and challenges in operationalising cascading translations of government programmes.

We sincerely thank Silvia Pilonato and the participants at the 10th EIASM Conference for the constructive comments provided during the conference and the accounting academics at UNSW and UTS for their feedback and support.

1.

In an earlier paper, Kurunmaki and Miller (2013) defined calculative infrastructures as “the relatively stabilised chain of accounting calculations and associated narratives …” (p. 1101).

2.

No minors were interviewed. Participants were aged 18 or over and reflected on their relatively recent school experience.

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