1 Introduction

In the first chapter of this book, I discussed that the starting point for the METRO project was an investigation of the emergent collaborations of International Organisations in the field of the production of metrics for transnational governance. The research project focused on an analysis of four case studies, on the measurement of education (on its global and European dimensions), on global poverty and on the rise of statistical capacity development, especially of statistical offices in the Global South. I described how, from the very start of the fieldwork, the notions of interplay and interdependence were instrumental to the analysis. In particular, what became quickly apparent was that quantification was not only made through the collaborations of large international organisations, but also that numbers had become the connective tissue of a large and ever-expanding governing architecture, what I and my colleagues have elsewhere described in detail as an ‘epistemic infrastructure’ of transnational governance (Bandola-Gill et al., 2022; Grek, 2022; Tichenor et al., 2022).

As a result, especially in the policy arena of education, METRO was dominated by the study of quantification in two major monitoring and policy initiatives: these were the Sustainable Development Goals (SDGs) and the making—for the first time ever—of the European Education Area (EEA). The SDGs, despite the slow progress towards their achievement, have been transformational in that they have truly created a global education policy space, where all participating countries, both from the North and the South, are monitored against their performance in a diverse range of indicators, from learning outcomes in literacy and numeracy, to gender equity and citizenship. In addition, for the first time ever, there has been a substantial shift in the geopolitics of the influence of large IOs in the field of education. Their collaborations and synergies have led to a much more fluid space of interaction, where older notions of a certain ‘territorialisation’ of zones of influence (OECD in the North, World Bank and UNESCO in the South) do not appear to hold ground any longer. Finally, as Chapter 6 outlined, the construction of a European Education Area is the first open proclamation of a unified strategy for the making of European education as a single policy arena. Despite the rule of subsidiarity that adjudicates education as a national matter (and thus not in the jurisdiction of the EU), the dominance of datafied governance across education stages and institutions has now allowed the European Commission to overcome political sensitivities, and support financially and strategically the construction of education as one of the key policy fields in the EU; numbers, of course, and all the calculative rationalities they created, have been the main motor powering this political and symbolic shift.

Although analysing quantification as the rise of an epistemic infrastructure—where the materiality of data is entangled with actors and networks (Bandola-Gill et al., 2022; Grek, 2022)—was a useful way to understand the paradigmatic changes that are taking place in the relationship of knowledge-making with governance, The New Production of Expert Knowledge is a fine-grained analysis of the constitutive qualities of expertise in the twenty-first century. In order to allow for such an analysis, the notion of the Mode 1 to Mode 2 knowledge transformation was key, as it was against its constituent parts that the findings of METRO were compared and contrasted. Although the idea of Mode 2 has been characterised as ahistorical, normative and ultimately part and parcel of the ‘governance turn’ at the end of the twentieth century, Mode 2 represented a key moment in re-thinking the relationship of knowledge production with governing, and thus became a popular idea that made traction not only in its own STS field but further afield, and particularly in the sociology of expertise. It is thanks to its usefulness as a thinking aid that it has taken such a central role in this book, breaking down the different constituent elements of the shifts in knowledge production and guiding the writing of each chapter. In what follows, I will return to these elements to discuss them in turn, before moving on to theorising how the new production of expert knowledge has become a key ingredient of educational utopia-making.

2 From Mode 2 to the Production of New Expert Knowledge in the Twenty-first Century

Before moving to the analysis of new developments in expert knowledge production, I would like to return to the outline of the ways Mode 2 worked as a productive springboard for thinking and analysing the making of expertise in the transnational governance of education:

Mode 1 Knowledge

Mode 2 Knowledge

Expert Knowledge

University context

Context of application

Global/universal level

Disciplinarity

Transdisciplinarity

Post-disciplinarity/Mono-disciplinarity (Economisation)

Homogeneity

Heterogeneity and Organisational Diversity

Brokerage/consensus/mediation

Autonomy

Social accountability and user reflexivity

Datafied accountability and expert reflexivity

Peer-review quality control

Extended quality control

The market of measures

Although the table format may imply an evolutionary or even comparative element to the relationship of Mode 2 and the making of expert knowledge, I do not wish to claim that expert knowledge qualities, as identified in the third column above, represent the further evolution of knowledge beyond Mode 2; the table is used merely as a heuristic schema which, although acknowledging that other contexts and spaces may display different characteristics in their knowledge/ policy relationship (Mode 2 or even Mode 1), at least in the field of the European and global governance of education, the story of expert knowledge production is substantially different than the one narrated by Mode 2. We will now look at these qualities in turn, in an attempt to make better sense of them.

2.1 Global Data for Universal Values

Despite the critique, the concept of Mode 2 science entailed an important point in theorisations of the relationship between knowledge and governance, which could be reflected in the debates over the focus on knowledge production in the context of application. The idea of producing knowledge across dispersed stakeholder groups and across multiple and diffuse institutional boundaries gained considerable traction as an antecedent of the idea of ‘co-production’ of science and policy. This idea was taken up by Sheila Jasanoff (2004) and is still relevant and increasingly popular in the production of research, and social science research in particular:

Increasingly the realities of human experience emerge as the joint achievements of scientific, technical and social enterprise: science and society are, in a word, co-produced, each underwriting the other’s existence. (Jasanoff, 2004, p. 17)

The idea of producing knowledge at the context of application entails a construction of knowledge that renders the boundaries between research users and producers insignificant (Wyborn et al., 2019). With co-production, this blurriness goes further, with the research process being designed collectively among producers and users (Bandola-Gill et al., 2023). Such knowledge production requires careful navigation between different values, objectives and epistemic frameworks in order to both assure the pluralism of voices involved in the process of knowledge co-production (Lövbrand, 2011) but also its ‘usability’ (McNie, 2007).

After the ‘participatory turn’ of major international bodies and institutions, the study of the production of expert knowledge for the transnational governance of education, poverty and statistical development revealed a space of interdependence and collaboration that for the first time brought together not only technical experts, but also a much larger group of data producers, users, donors and national officials. These linkages and new entanglements encapsulate the enhanced role of a growing number of actors—from the UN agencies and member states, to philanthropic and civil society organisations and the academia, all participating in the production of global governance, not only at the decision-making level, but also in technical meetings and exchanges. These complex relationships happened through and around numbers, which both stabilised the connections, as well as mobilised and created new constituencies and new interdependencies. Given the enhanced role of diverse actors in technical meetings and decision-making for determining the terms and conditions of ‘governing by numbers’, quantification emerged as a fruitful arena for collective puzzlement, socialisation and policy translation. Although in most cases it is the objectivity of numbers that is considered central for ‘governing at a distance’ (Cooper, 1998), governing the global education policy field intersected with two other elements; these are the notions of symbolic space and belonging. Space is crucial, because the transnational participatory turn, contrary to other sites of audit and accountability, necessitated meetings at specific physical and online places. This is important to keep in mind, since often the discussion around numbers, standards and performance management appears as relatively abstract and top-down, therefore, missing out on an understanding of the role of meetings that bring together a community of people. On the other hand, we saw that progressively—and even in politically and historically distinct, at times even hostile, organisations, such as the relationship between the OECD with the European Commission, or the World Bank with UNESCO—socialisation led to belonging; this concept was relevant to the analysis, as contestations were counterbalanced by a sense of universality and rapport, ‘mobilised by institutions in their struggles over acceptable political practice’ (Cooper, 1998, p. 16).

Still, how can one contemplate that the cold rationality of number-making could ever lead to such collective declarations of belonging? The book charted the significance of numerical inscriptions in the production of shared narratives and global values. Chapter 2 discussed how global and European monitoring exercises are not merely technical exercises but discursively address some of the most complex, interlinked and compounded global challenges that the world currently faces. Indeed, dystopian numbers became affective tools in the arsenal of persuasion devices for IOs’ experts. Therefore, the production of numerical narratives that describe these very fluid and often dangerous phenomena is needed all the more; while trying to make sense of these emergencies, narratives also offer some (even momentary) stability and hope. Finally, numerical narratives do not need to be precise; thus, they offer added legitimacy to numbers, while masking data gaps and technical inaccuracies. According to Roe, a narrative stabilises ‘the assumptions needed for decision making in the face of what is genuinely uncertain and complex. They can be representationally inaccurate—and recognisably so—but still persist, indeed thrive’ (1994, p. 51).

Above all, in the field of the global governance of education, contrary to the Mode 2 argumentation, contextualization (or the context of application) does not appear relevant. Instead, what we see is the articulation of global values into local ones. In the space of the global governance of education, extended as it has been with the participation of national and local actors and agendas, the local is erased, as it is translated into—or sidelined by—global, universal values that bind all actors, numbers and narratives together in a discursive mix. In other words, and perhaps counterintuitively, the global has become the local and vice versa: this is the new doxa of the universality of education problems and solutions that appears to guide most of the production of expert knowledge and education policy in the twenty-first century.

2.2 Monodisciplinary Visions of a Complex Education World

One of the key transformations of Mode 2 knowledge production was the idea that knowledge had to break free from the siloed disciplinary confines and be synthesised with other knowledge in order to be relevant and effective: this was the move towards transdisciplinary knowledge production, which gained particular traction in the evidence-based policy literature, as almost a pre-condition of solving the wicked super-crises beholding societies. As if transdisciplinarity were not hard to achieve in the first place, most knowledge producers (and funders) moved on to an emphasis of the benefits of interdisciplinarity, as the need not only to bring together but also to synthesise and combine disciplinary perspectives grew (though, admittedly this was not what Mode 2 proclaimed). According to the supporters of interdisciplinary knowledge production, global challenges require the combining of methods and insights from multiple academic disciplines in order to resolve the multifaceted and complex ‘wicked’ problems of the twenty-first century, such as inequalities or sustainability. Education, with its close relevance to a number of social processes, problems and opportunities (for example, its links to citizenship, democracy, sustainability, labour markets, inequalities, well-being, health, innovation and others) were to benefit most from such a synthesis of expertise in order to address complex social issues; as we have seen, however, this is not what happened.

Instead of trans/interdisciplinary knowledge, the production of new expert knowledge in the field of the global governance in education is characterised by mono-disciplinarity. This is the rise and dominance of economics, as the only relevant disciplinary field that would bring such diversity of actors and their interests together. The supremacy of economic versus any other knowledge in the global governance of education is of course not new. It can easily be traced and explained by the key role that at least two major international organisations played in the formation of the field of transnational education and the education indicators and data that shaped it: these are the Organisation for Economic Cooperation and Development (OECD) and the World Bank, both well-known for the close links that they draw between education, economic growth and human capital development. Similarly, the European Commission, despite its support for education for the promotion of social cohesion and a ‘people’s Europe’ (Grek, 2008; Lawn & Grek, 2012), has not shied away from its emphasis and support for education as a key driver for the making of a prosperous and competitive ‘global Europe’.

To be clear, my argument does not refer to the economisation of education as the well-rehearsed analysis of neoliberalism and its effects on education over three decades and more; although this form of critique is still relevant, it has been developed eloquently in previous research (Barrett, 2011; Mundy et al., 2016; Tikly, 2015). What mono-disciplinarity means in the context of the global governance of education, is the sole dependence of education as a policy field on economic epistemology and methodology as a way of mapping, knowing and planning education for the future. Although arguably this dependency cannot be decoupled from the historical roots of the construction of a commensurate global education policy field by international organisations that prioritised economistic perspectives (and specifically neoliberal economic values) (for a comprehensive analysis, read Elfert & Ydesen, 2023), it is important to pay attention to how economics shapes the production of expertise in education and what the effects are for knowing and governing the field.

As discussed in Chapter 3, although interviews with education experts revealed some differences among them, they all shared one common characteristic: that is, their disciplinary background was in economics. In the early decades of the production of education indicators (1970s and 1980s), it was education economists that pushed for the idea of building comparative education datasets, in order for major economies to compare and compete in terms of education performance for economic prosperity. Later, at the turn of the century and into the 2000s, as we saw in Chapter 3, it was again education economists, such as Hanushek (2000) and Glewwe (2002) that led to the paradigmatic shift from the measurement of inputs to outputs in education (Grek, 2022). As METRO’s fieldwork revealed, many of their disciples continue to dominate the field; although working in the field of education, when asked about their studies, they all responded that they had economics degrees.

Although education economics is a needed and long-standing way of doing comparative analysis in education, it is the singularity and prevalence of economics as a vision, a way of thinking and analysis that is of interest here: following its epistemology, education processes and institutions are framed as economic entities with unlimited possibilities for growth and improvement (Miller & Power, 2013). A focus on economics as a way of structuring and comparing education data ‘implies a concern with the idea of efficiency (Kurunmäki et al., 2016, p. 396), as well as the aim to create and expand the education ‘market’ (as we saw in Chapter 6), and an emphasis on competition and performance (Caliskan & Callon, 2009). Last but not least, in education but also a multiplicity of other areas of political and social life, the prevalence of economics and the economisation of knowledge production that followed it, has led to the financialisation of education actors, processes and institutions, calculated as assets in a capital investment market that is hoped will create returns (Chiapello, 2015; Muniesa et al., 2017); post-COVID, such processes of assetization have intensified following the increasing digitalisation of education and its services.

In a world of increasing and compounding challenges, how come the global governance of education has become so dependent on the mono-disciplinarity of economics? It is in the role of quantification that the answer has to be found, in what looks increasingly like a chicken and egg question. Mennicken and Espeland are beautifully eloquent in their description of the relationship of quantification with economics; their analysis could easily work as an accurate description of the education condition for more than half a century now:

Quantification and commensuration are key conditions for economic calculation and action. Quantification makes individual and organizational performance visible, trackable, and comparable, thereby allowing for organizing in accordance with principles of efficiency. (2019, p. 240)

2.3 Perfect Brokers of Imperfect Numbers

Mode 2 knowledge proponents suggested that, as social problems become increasingly ‘wicked’, no one source of expertise is sufficient to solve policy issues (Baekkeskov, 2016). Consequently, as highlighted by Nowotny et al. (2003, p. 155), new challenges require ‘socially distributed expertise’—one which is decentralised and blends multiple sources of knowledge and actors sourcing evidence. Such plurality of expertise was not seen as limited to elite knowledge producers, but would also include localised ‘lay’ experts and experts outside of academia, where the traditional scientific knowledge was produced.

At the same time, the key tension in identifying expertise in high-risk settings cannot be reduced to simply adding new forms of expertise to the equation, but rather requires the emergence of new, different forms of expertise altogether (Eyal, 2019). Such transformations to the nature and role of expertise were also a result of what was seen as its high-context relevance and thus its inherently ‘local’ nature (Wyborn et al., 2019)—a characteristic that was also understood to be contradicting the rise of increasingly global challenges.

Although the METRO interviews revealed a diverse field of actors participating in the production of monitoring agendas, IOs’ experts have continued to occupy a central role. Their expertise consisted primarily in the evaluation and harmonisation of datasets, as the latter were produced by national and international assessments, and more crucially in their ability to use their epistemic capital, as well as their socialisation skills in order to broker knowledge between actors and fields and persuade participants about the benefits of their involvement. After the participatory turn that the SDGs brought, and following similar developments at the European education policy field where measurement agendas have to be politically acceptable to all member states involved, expert work has evolved to include more than simply the production of robust data. Instead, the principles of democratisation and technocracy are considered indivisible and thus leading experts to apply their mediation skills in order to first, secure country ‘buy-in’ into the monitoring frameworks; second, navigate local politics and requirements, especially in cases of countries of the global South where needs for the collection of global, comparable data do not match local budgets and needs; and finally, to succumb some of their technical robustness to the politics of producing ‘good enough’ data (Fontdevila, 2023), so as to allow the process to continue and a level of minimum consensus to be found.

Such brokering and mediating work depended on experts working to maintain a tight balance between retaining their epistemic superiority and scientific credentials, while combining these virtues with the crucial political calculations of how to secure (and maintain) participation and buy-in, create consensus and make sure that the numbers’ work continues apace: that is, despite the imperfections of ‘bad’ quality data, experts have the—often impossible—task of producing indicators that are acceptable to governments, fit their existing local data structures, while also being comparable globally and reaching a minimum level of technical quality. Dealing with the implications of having to balance out the technical and the political challenges of doing expert work, experts’ brokering practices were aided by the use of ‘imperfect’ numbers (for a fuller discussion of the distinction between ‘ambiguous’, ‘placeholder’ and ‘provisional’ numbers see Chapter 5 in Bandola-Gill et al., 2022) which, as we saw in Chapter 4, counterintuitively transformed IO actors into more trusted experts than those who depended solely on their epistemic authority to maintain their influence and trustworthiness in the field. Although it is quantification that brings all actors, narratives and numerical inscriptions together, expert work has transformed to adapt to a much broader conceptualisation of what epistemic authority entails; that is, moving beyond the objectivity and scientific robustness of numerical work, quantification, through the experts’ work that carry it, appears to be folding both the science and the politics of numbers in its processes, thus expanding and re-inventing what ‘trust in numbers’ in the twenty-first century entails.

2.4 Reflexive Experts of Datafied Systems

In tandem with the making of knowledge within the context of application, Mode 2 suggested that contemporary knowledge production cannot be autonomous any longer (knowledge for knowledge’s sake) but has to be socially accountable and reflexive: in other words, knowledge producers need to be accountable to the communities that they belong, i.e. produce knowledge that is understandable and justifiable by its users. Further, it was understood that such socially accountable knowledge production would also lead to increasing levels of user reflexivity, in relation to the knowledge produced.

Nonetheless, what the last three decades in the field of the global governance of education have shown is not the emergence of socially accountable expert knowledge production, but rather a much more technical, performance-based accountability that saw the rise of an assemblage of formal and informal procedures, various techniques, assessments, tools and normative discourse, aiming at making education systems accountable (by making them comparable) for improving performance. This form of performance-based accountability is dependent on the prevalence of datafication, that is, on quantified data that originates from local and national testing, other forms of evaluation and comparison and is eventually translated into performance indicators and global measurements of learning data. Datafied accountability can thus connect and interlock several scales, from local and sub-local levels, to the national and the global and is the key ingredient of the rise of ‘expertocracy’ in education (Grek, 2013). From the 1980s/9s New Public Management and the emergence of high stakes testing, all the way to the rise of international comparative assessments and the datafication of education, performance-based accountability is the outcome of historic, contemporary and social constructions that result in the selection, bricolage and translation of datafication in education policy globally (for a more extensive discussion of accountability and datafication, please see Grek et al., 2021).

The rise of datafied accountability has become the day-to-day reality of all education systems around the world, with severe repercussions on schools, students, parents and the teaching profession. It is a story that education researchers have told and, as the METRO findings showed, one that has increasing impact on experts’ reflexivity, as they observe the limitations, challenges and often the countereffects of almost half a century of education datafication. Chapter 5 discussed how surprised the research team was to find such a heightened sense of reflexivity among experts, who openly discussed not only the difficulties of their task, but also the political nature of data production. During the 100 + IO expert interviews that we took, we found increasing numbers of experts who were revealing about the challenges of bringing together technocratic and participatory modes of decision-making. Experts discussed the difficulties of finding appropriate data and datasets to match the selected indicators, given that the latter were not decided on the basis of what was technically possible but were merely political aspirations and declared policy goals; many of them shared their frustrations of the ‘endless’ consultation processes that took over their technical meetings. Lastly, as I discussed, experts in the field, and particularly those that aimed to capitalise from their long-standing relationships with countries in the global South, rather than their technical credentials, used reflexivity instrumentally, proclaiming the benefits of pushing the agenda on, even if they had to do so on the basis of imperfect or approximate data. Indicators, as they suggested, were never meant to be accurate; they are to be used as ‘barometers’ of countries’ progress rather than precision tools (Montoya, 2017).

Thus, instead of social accountability and user reflexivity, expert knowledge production in the twenty-first century has for a long time now followed a path of performance management and datafication; the repercussions of these trends are reflected in the reactions against them, leading to what I have discussed as the increasing democratisation and the participatory turn in global governance. Through such processes of widening the field of actors, of democratising the agenda and of using numerical narratives and affective scripts, expert knowledge producers have become a lot more reflexive of their work and its challenges. Using epistemic reflexivity to talk about the unintended consequences of quantification, or even applying reflexive practices instrumentally in order to enhance their persuasive power, experts appear more and more to be producing knowledge because they care for the communities and the issues they work on. They may be technocrats, with specific educational paths and career trajectories, but they can also be ‘prophets, saviours and saints’: that is, they measure the present and forecast the future with the aim to save lives, despite the challenges and out of a sense of morality and altruism towards those mostly in need (as I have discussed elsewhere, see Grek, 2020). Therefore, the opening out of the field of the transnational governance of education revealed an expert knowledge production that is highly reflexive, dialogic, self-critical and open to contestation.

2.5 The Market of Measures

Mode 2 suggested that the quality control of new knowledge production was not only limited to the traditional peer review mechanisms that scientific knowledge has always been submitted to, but also that the quality control was more extended and dispersed, including its users and the wider public. Given the move to more transdisciplinary and contextualised knowledge production and application, such a shift to how the quality of knowledge was assured was seen as the direct consequence of the wider transformations taking place in society.

Expert knowledge production in education has also seen such a broadening out of the quality controls that establish its worth. Although it experienced a long period of dominance and success of certain measures (see OECD’s PISA for example, which ruled media headlines and education ministers’ desks for at least a decade), what we see as a direct consequence of the production of SDG4, is a competition of measures. Most IOs, although working collaboratively, are also eager to promote their own institutional brand and thus operate simultaneously at two levels: on the one hand, they appear as open to alliances and working collaborations towards ‘the goals’, while on the other they are also conscious of needing to maintain their independence and unique contribution to the field. These double roles create contestations and lack of trust and may derail negotiations in what is already a very fragile governing field. Within Europe, the market of measures is also growing: here, I examined the production of quality assurance in higher education in Europe and showed how a project that began developing around the Bologna process twenty years ago, has now grown into a fully blown quality assurance industry, with a growing number of actors and datasets competing for attention and funding. As some of the key figures in the global governance of education discuss (see Chapter 6), this is a market of measurement, with inefficiencies and paradoxes, but also sellers, buyers and sale pitching events for determining which ‘product’ best fits the work of policymakers. Given the influence of private capital in education and—especially post-COVID—the proliferation of major education consultancies and platforms, the market of measures and data producers is only bound to inflate and become more competitive. However, Chapter 6 does not ask whether there is a market of education data providers or not; we have known for some time that it exists and that it is thriving. Instead, the focus of the argument is that, instead of collaboratively working towards producing the most robust measures for the calculation of global learning data, selecting measures appears more like a ‘pick-n’-mix’; governments and IOs select the measures best suited to the budget, their policy priorities and above all, the way the measures portray their performance.

To conclude this section, the transformation from Mode 1 to Mode 2 knowledge production promised a much more open and horizontal field, where knowledge was to be applied, contextualised, transdisciplinary and led by user demand. Consequently, an examination of the qualities of expert knowledge has become increasingly complex, as the criteria of assessment are dispersed and often contradictory depending on the stakeholder. The moves towards Mode 2 knowledge production have led not only to the democratisation of knowledge by increasing the plurality of actors involved in the process of knowledge production (Nowotny et al., 2001), but rather also to the commodification of knowledge and its assessment purely in utilitarian sense (Ozga et al., 2011). Yet, despite the tensions between the production of authoritative, ‘usable’ expert knowledge and the critical, up-stream engagement of stakeholders with it (Lövbrand, 2011), quantification persists as the only viable means by which to plan and prepare for a better world of free and equal education for all. Despite the fairly bounded, national responses to the major education crisis that the recent global pandemic brought to the fore, it is clear that COVID-19 has acted as an accelerator for the re-making of datafied and digitised education governance in the twenty-first century. Building on discourses around the ‘devastating impact’, ‘learning losses’ and yet another ‘lost generation’ that COVID-19 may have brought (Brookings, 2023), global education experts try to tame the current condition of radical uncertainty by inscribing the future into calculable horizons. The next and final section of this book discusses the role of quantification in the promise and the crafting of utopian futures of education that have never been.

3 Education, Quantification and Utopia

Utopias are not new in education. From Plato’s Republic to the critical pedagogy of Paulo Freire, the dream of creating an alternative society, free from oppression and inequality and guided by critical pedagogy, has been at the centre of educational thought and action for a very long time. In this concluding section of the book, I discuss how quantification, from a technocratic and a-political mode of informing policy with evidence, has slowly been transforming into a mode of utopian thinking—a way of seeing, constructing and performing the ‘desired possible worlds’ of the future (Levitas, 1990). Here, I do not examine utopian thinking as the practice of dreaming education unicorns and sunlit uplands, which is a frequent criticism of the term. Instead, I follow Jameson’s ‘Politics of Utopia’ (2004) and Levitas’ ‘Utopia as Method’ (2013) to reflect on the ways that quantification has not only adopted elements of forecasting and planning ideal future worlds, but also that the processes of number-making have acquired the social and political function of co-constructing alternative and utopian education panoramas.

In particular, this book has built on theorisations of numbers as performative, i.e. constructing rather than simply measuring political phenomena (Kingsbury et al., 2012; Mehrpouya & Samiolo, 2016; Porter, 1995) in order to show how, quantification is increasingly integral to the making of contemporary utopian education thought. By using the frame of ‘utopia-making’, I refer to the predominance of the co-construction of ambitious political and education imaginaries via numbers. The analysis of the making of the SDGs, as well as the production of a single and unified European education area, reveals numbers as central to the making of utopian visions of interconnected education policy futures, rather than merely representing sets of isolated targets and policy recommendations, as previous global tools like PISA or the MDGs involved.

In particular, this book has shown how older arguments about the de-politicisation of numerical work have now been replaced by its re-politicisation, as the politics of numbers are not hidden any longer, but legitimised on the basis of their transformation into the new spaces for democratisation of decision-making. Elsewhere I have charted the ways that the rise of an epistemic infrastructure in global public policy has led to the paradigmatic shift of the recalibration of measurement and governing as co-constructed: measurement and the production of expertise are advocated and utilised as key spaces for achieving political consensus and for shaping public policy directions (Bandola-Gill et al., 2022; Grek, 2022). In a post-truth world, flooded with data and mistrusted numbers, expertise had to transform and adapt to these new political and social realities; these developments were strengthened further through social movements such as ‘Black Lives Matter’ (Strickland, 2022), #MeToo (Hillstrom, 2019), the rise of decolonial discourses (Bhambra, 2014) and the threat of climate change. Thus, as the pages of this book have revealed, expert knowledge production has assumed functions that would have been previously unthinkable. Instead of merely informing policy, expertise has become the platform for envisioning new ways of doing governing: interpretative flexibility, openness, (re)politicisation, reflexivity and democratisation are key discourses and proclaimed aims for the new governing and expert knowledge paradigms of the twenty-first century. Thirty years on from The New Production of Knowledge (Gibbons et al., 2010), quantification is not merely a tool in the arsenal of policy instrumentation and change; instead, quantification has been institutionalised as being at the very core of governance itself.

Although these phenomena and their management are of high significance in contemporary governance practices, here I analyse specifically the role of numbers as the key building block in the making of utopian education futures. Indeed, as we have seen in the pages of this book, measurement and the making of expert knowledge more broadly, have moved beyond achieving mere prediction and ‘readiness’. Rather than offering the reading of a crystal ball, narrating the future involves establishing a discursive agenda of the education values of the present, and the ideas and ambitions of how education futures will be shaped. In bringing together these futuristic ambitions and goals (‘ensuring inclusive and equitable education for all’ for example—the education SDG), narrating the future represents a governing manifesto of contemporary considerations, uncertainties and potentialities. By quantifying these education futures, actors in European and global education governance establish a common utopia of political goals, the progress of which can be carefully measured and supported by policy reforms.

However, how can the post-COVID, crisis-ridden education policy arena have fostered such ambitious education plans? The book, through its analysis of numerical narratives, networks of actors, meetings, data harmonisation processes and aspirational policy declarations, showed how quantification serves as the springboard for the ‘utopian leap’: that is, the quest for numbers counteracts the paralysis of a dystopian reality and fills the gap between the dreary present and the ideal arrangements of a desired future. Thus, the ‘promise and dream’ of quantified future-making is grounded on a central condition: utopia does not only offer the imaginary of an ideal world, but it is also—and crucially—inherently procedural (cf. Thaler, 2019): in other words, through the establishment of the processes of indicator making, data harmonising, actor meeting, report writing and many others, the work of producing the future is being done. This is what Ruth Levitas (2013) coined as ‘utopia as a method’—one that is not only about imagining better worlds, but also a mode of action. In addition, through the imagining of alternative realities, utopias necessarily encourage a reflection on the current state of the world. Indeed, recent scholarship on utopianism offers a more nuanced understanding of the relationship between utopias and reality. The most important work aimed at merging the two, rather than contradicting them, is Erik Olin Wright's ‘Real Utopias Project’. As argued by the author,

What we need, then, is ‘real utopias’: utopian ideals that are grounded in the real potentials of humanity, utopian destinations that have accessible waystations, utopian designs of institutions that can inform our practical tasks of navigating a world of imperfect conditions for social change. (Wright, 2010, p. 6)

As I argue in this book, the new expert knowledge production for global governance, re-imagined and re-organised as a common space for technical and democratic accountability, represents an example of ‘utopia as method’: by painstakingly drawing a multiplicity of indicators and actors together, they outline these ‘waystations’ for all participant countries as the only realisable—and available—path to a better future. Ruth Levitas suggests that the utopian vision may foster conditions for thought, debate and experimentation (1990): as I have shown, meetings and data collection practices ostensibly create spaces for exchange, no matter how unequal and asymmetrical they may be. Further, they also appear as helping facilitate criticism of the current reality—in the context of global governance, such criticism does not only relate to the state of the world per se, but also what has been seen as the continuous colonial project of the global North determining the future of the global South (see Boldero & Francis, 2002). As we have seen, the demands for democratisation and decoloniality have destabilised the older balance of power among IOs and created new opportunities for previously weaker IOs to gain new influence (as the example of the UNESCO Institute of Statistics has shown—see Chapter 5).

However, as the analysis showed, for quantification to represent a new mode of political imagination, utopias of imagined future education worlds have to be coupled with dystopian thinking. Dystopias are inherently grounded in a ‘cautionary pedagogy’—a warning about the state of the world and its future. As such, dystopias play a specific role in galvanising actors involved in dealing with a crisis (Thaler, 2022). The goal of a dystopia is to imbue utopian visions’ ‘wishful thinking’ into pragmatic and—in the case of quantification—technocratic and process-based modes of inquiry, thus rendering utopian visions as problem—rather than idea-oriented (cf. Gümusay & Reinecke, 2021). Jameson could not have phrased this better: utopia-making represents ‘model railroads of the mind’, the continuous ‘bricolating and cobbling together things of all kinds’ (Jameson, 2004). This is utopian thinking as ‘miniaturization’: that is, ‘replicating … things in handicraft dimensions that you can put together by yourself and test … or change and rebuild in a never-ending variation fed by new ideas and information’ (Jameson, 2004, p. 40).

Thus, it is the material and procedural character of utopian thinking that aligns it so closely with the analysis of expert knowledge production for governance. As I have shown in detail in the previous chapters, expertise, with its novel qualities of universalism, mono-disciplinarity, brokerage, reflexivity and marketisation, created a more fluid space that assembled a broad church of actors, ideas, methods and interests. The intertwinement of these infrastructural elements came together, time and again, in smaller or bigger ways, to create perfect versions of an evidence-focused, goal-oriented, utopian future. By ‘coming together’ I do not intend to say that these processes were harmonious, frictionless or equal in any way. The analysis of the production of European and global learning data is a space of struggle and contention, where numbers facilitate debate and cause discord, but also that, at critical junctures of the process, worked to achieve at least a minimum consensus over goals and priorities, so as to protect the place of education as a key policy arena in the field of the global governance of sustainability and economic growth.

Perhaps the most notable affordance of quantification to create spaces of educational consensus has been the quality of numbers to be malleable and moving, rather than fixed, entities. Rather than valuable for their objectivity, collecting data for education indicators became a process of finding ‘good enough’ data solutions for the short term: these could be ambiguous numbers, or what interviewees called ‘placeholder’ or ‘provisional’ numbers—and their value rested primarily on their ‘strategic ambiguity’ (Sillince et al., 2012). Such ambiguity of the contested indicators enabled them to act as boundary objects, almost in the original meaning of the term (Star, 2010): that is, it allowed for different interpretations and actions between different groups, without necessarily solving the conflict among them, but facilitating the continuation—and even bolstering—of number-making. This process of widening participation in the decision-making around indicators and quantitative targets is a focal point not only as a matter of achieving equity, but also—and perhaps primarily—as a route for enhancing political buy-in into the infrastructure of measurement. Therefore, the previously technocratic process of developing and validating indicators has transformed into a forum for the construction of socio-technical imaginaries of a common, utopian future, carefully balanced between idealistic orientations, but also concerned with realism-driven expectations of feasibility. It is this interplay between idealism and pragmatism that quantification has achieved; trust in numbers bridges the promise of accountability and scientific authority with the political demand to create the—so-called at least—‘bottom-up’, collective and ambitious futures for the planet.

To conclude, despite their failures, European and global monitoring agendas and their expert producers have not lost their relevance, as they continue to dominate the global political debate around the need to ameliorate the chronic neglect and exploitation of both the environment and of vulnerable populations around the world. The exceptional global temperatures, rainfall and draughts of recent years are only signals that the global pandemic may not have been the worse humanity has experienced in the first half of the twenty-first century. This book discussed the ways the new production of expert knowledge represents social and political endeavours to rationalise and ‘technicize’ the process of offering education for all. It also discussed the ways quantification as utopia has overshadowed and monopolised any other spaces and modes of political imagination, as it proclaimed to offer technical and measurable ‘waystations’ in imagining and planning for education futures. This is because, as Miller contends,

the future does not exist in the present but anticipation does… To use the future is strictly speaking, not possible, since the future does not exist as an object or tool to be used. The future as anticipation, however, is continuously instrumentalised. (2018, p. 59)

Thus, quantification in global governance captured the imagination of a wide set of actors, since it purposefully allowed multiple ‘entry points’ in its world: although experts continued to emphasise the use of technocratic and management principles to create an objectified and measurable field (and hence still appear authoritative, accountable and in line with scientific approaches to policymaking), quantification is equally now being proclaimed as the space for bottom-up, grass-roots and transformative education politics. Despite power differentials, as well as tensions and disagreements, a common global education policy field has been created, making quantification the common policy language in the process. Ultimately, as we have seen, the production of quantified utopian futures, as the only option to avoid catastrophic dystopias, may have little to do with the future itself: rather, it offers productive tools to make sense of and tame an increasingly ungovernable, crisis-prone and fast-moving educational present.