Research in a time of metadata, Big Data, data curation, data mining, data science, etc.

I intended the last entry (30 May 2022) to trouble a common conceptualization of “data” as straightforward facts and information that can be marshalled to prove all sorts of things. I argued that the destabilization of this conceptualization can be accomplished by recognizing both how “data” are social products and how they participate in governing practices that produce “realities”. 

Such a stance recognizes “data” as necessarily political – embroiled in social relations. Mol (2002: 155, emphasis in original) says as much in her insistence that “Methods are not a way of opening a window on the world, but a way of interfering with it. They act, they mediate between an object and its representations”. She follows up this proposition with this advice to PhD students: we ought to consider “not what we want to know”, but “what we want to do”. As Mol (2002: 151) puts it, “veracity is not the point. Instead, it is interference”. 

Springgay and Truman (2018: 206) develop a similar argument. They question “a reliance on data modelled on knowability and visibility”. The point of research is not “reporting on the world” but “doing rather than meaning making”:

“What has become increasingly clear is that rather than trying to collect data or represent an objective reality (methods that privilege the human and treat data as existing phenomena), we need to think about inventive practices that ‘intervene, disturb, intensify or provoke a heightened sense of the potentiality of the present’ (Sheller, 2014, p. 134)”. 

This approach requires a different orientation to methods” (Springgay and Truman 2018: 206) in which “particular (in)tensions need to be immanent to whatever method is used”. 

The form of this challenge to conventional research approaches needs to be elaborated. It is beyond uncommon for researchers to declare that they do not wish to produce knowledge. To embrace such a project puts students in a precarious position in relation to acceptance of their work. As Koro-Ljungberg and MacLure (2013: 219) describe, 

“the concept of data is generally treated as being unproblematic. Data are simply regarded as something we collect and analyze in order to arrive at research conclusions. Data has become a key element of one of the main grand narratives of research”.  

St Pierre (2016: 116) helpfully locates this stance on “data” within a history of logical positivism, which endorses an empiricism grounded in mathematics: 

“Logical empiricism strongly influenced natural science, social science, and philosophy in the United States until the 1960s when its premises were critiqued, for example, by interpretivism, social constructionism, critical theories, and the ‘posts’ [e.g. post-structuralism, post-humanism, etc.], and it fell out of favor”. 

This situation changed in the new century when “logical empiricism returned with a vengeance in U.S. education with a neopositivist description of scientifically based research in education (see St Pierre 2006)”. According to St Pierre this neopositivism now dominates educational research and practice, and many social science disciplines – including psychology, political science and economics.

St Pierre (2016: 111) identifies a second empiricism operating in conventional social science methods, an “empiricism of phenomenology” that privileges “experience as the primary source of and justification for knowledge”. Here empiricists “insist on facts supported by sense impressions or brute datum found through careful observation of experience (experiment) to justify knowledge claims”. 

We can see the playing out of these intellectual developments in the debates about quantitative versus qualitative research, and the frequent endorsement of “mixed methods” (Bryman 2006; see Research Hub entry 31 August 2021). Meanwhile, the contemporary focus on “evidence-based policy” and on “what works” signals the enduring strength of “scientifically based research” (Bacchi 2009: 252-255). Social sciences struggle for legitimacy in this climate, indicated I suggest in the metaphorical adoption of “data” to describe qualitative research materials (see previous entry). 

More recent post-qualitative research approaches bring a distinctive perspective to the issue of “data” and “authenticity”. These approaches challenge both a correspondence view of knowledge (see last entry) and the privileging of human actors in research practices. Springgay and Truman (2018: 206) draw links between post-qualitative arguments and the “new materialisms” in the determination to de-privilege human actors while incorporating an understanding of matter as “lively”. In post-qualitative inquiry there can be “no post qualitative data or methods of data collection or methods of data analysis”. For St Pierre (2016: 113), with Leonelli (2014: 1), “there is no such thing as direct inference from data”.

Because conventional humanist qualitative methodologies draw heavily on phenomenology and the humanist subject, and because their methods-driven approach also draws heavily on logical positivism, St Pierre concludes that they cannot accommodate the new post-qualitative perspective. On these grounds St Pierre (2016: 122) calls upon researchers to try to forget their training, to put “methodology aside” and, instead, to read “widely across philosophy, social theory, and the history of science and social science to find concepts that reorient thinking” (St Pierre 2019: 10).

In a previous entry (31 May 2019) I tried to take a tentative step away from the depoliticizing implications of this apparent abandonment of research methods. There I suggest that critical ethnography (see also entry 28 Feb 2019) and a determination to interrogate our concepts (self-problematization) create room to explore the possibility of adopting “a wide gamut of empirical techniques, as part of a commitment to selected political goals” (Bacchi and Goodwin 2016: 23; see Tamboukou and Ball 2003). I proceed below to make a similar case for engaging with (not “using”) “data”. To engage with data requires research attuned both to how data is produced and to how it is productive (constitutive), as argued in the previous entry (30 May 2022). I now proceed to draw attention to some innovative work that takes on these tasks.

Patti Lather (2013: 643) notes that the “age of big data” and the “march of quantification” are not going away. In this setting Geoffrey Bowker (2013: 170-171) insists that “If data are so central to our lives and our planet, then we need to understand just what they are and what they are doing”. To this end Cambrioso et al. (2014: 20) argue that “social scientists can enter into a reflexive relation with the entities they analyze”. To do this Leonelli (2017: 195) recommends that “we attend to the negotiations regarding what counts as data, for whom, when, where, why – and how this changes – and what is regarded as missing in such processes”.  

Fordyce and Jethani (2021) have begun to develop an analytic heuristic or tool to undertake this form of analysis. They start from the notion of “data provenance”, which attends to the origins of a piece of data and to the methodology by which it was produced. They proceed to ask additional questions about that data in a method they call “critical data provenance”. The additional questions address “who”, “what”, “when” and “how” data are produced and operate, producing a history (or genealogy) of datasets. Fordyce and Jethani (2021: 3) argue that this framework expands “beyond the technical to act as an analytical ethics tool for thinking about transactions in data and their consequences” (see also Beer 2016). 

QuantCrit, a methodological sub-field of Critical Race Studies in education, develops another “toolkit” to rethink and engage with “data” (Gillborn et al. 2018: 169). Researchers adopting this approach argue that “quantitative methods cannot be adopted for racial justice aims without an ontological reckoning that considers historical, social, political, and economic power relations” (Garcia et al., 2018: 149). To this end they develop a set of principles through which it becomes possible to re-imagine and “rectify” “data”:

       “(1) the centrality of racism

       (2) numbers are not neutral

(3) categories are neither ‘natural’” nor given: for ‘race’ read ‘racism’ 

(4) voice and insight: data cannot ‘speak for itself’

(5) using numbers for social justice” (Gillborn et al. 2018: 175).

Street et al. (2021: Abstract) usefully bring together QuantCrit principles, Indigenous Standpoint Theory and WPR “to elicit hidden assumptions within the use of statistics to measure the success of Indigenous higher education policies in the NT (Northern Territory)” in Australia.

My colleague Jennifer Bonham and I (2016) have taken on the specific task of how to deal with interviews as research material. We take up the challenge posed by St Pierre (2011: 620) in her critique of humanist research methods that rely on “a disentangled humanist self, individual, person”. To move past this obstacle to poststructural use of interview material we develop a methodology, referred to as Poststructural Interview Analysis (PIA), that treats “subjects” as provisional and in process. This approach allows us to shift the focus from trying to understand why the interviewee says what s/he says to the conditions that make it possible to say certain things, how those things are rendered “sayable” (Bacchi and Bonham 2016: 116). These “things said” are studied in terms of what they produce, or constitute, rather than in terms of what they mean (Bacchi and Bonham 2016: 118). Unsurprisingly, nowhere do Bonham and I refer to “interview data”.

In a Guest Editors’ Introduction to a Special Issue of Cultural Studies, Critical Methodologies – called simply “Data” – Koro-Ljungberg and MacLure (2013: 219) raise the possibility of “more active and significant roles for data”. In doing so they challenge the “subordinate or supplementary role” commonly assigned to “data”. That is, “data” seem to get their power from being seen as inert, as “evidence” that simply needs to be marshalled. Questioning the conceptualization of “data” as simply “facts” and “information”, therefore, opens up opportunities to find ways to deploy “data” creatively. 

Latour et al. (2012), for example, show that databases can play a role in questioning an agency/structure dichotomy, which has dominated and constrained sociopolitical thinking. In the place of that dichotomy they elaborate how the proliferation of data can point to the importance of “actors-networks” (2012: 607):

“It is because those databases provide the common experience to define the specificity of an actor as tantamount to expanding its network, that there is a chance to escape from choosing between what pertains to the individual and what pertains to the structure” (Latour et al. 2012: 612).

Along similar lines, Lather (2013: 639) shows that what “data” make available allows researchers to replace binaries with continuums and multiplicities. 

Latour el al. (2012: 612-613), of course, are well aware that data bases 

… are full of defects, that they themselves embody a rather crude definition of society, that they are marked by strong asymmetries of power, and above all that they mark only a passing moment in the traceability of the social connections.

Still, they believe “it would be a pity” to miss the opportunity to explore “another way to render the social sciences empirical and quantitative without losing their necessary stress on particulars”. 

Between 2006 and 2009 my colleague, Joan Eveline, and I worked closely with “data” in a project on gender analysis (see Bacchi and Eveline 2010). The reference group for the project, which included academics and policy workers, provided a space in which to discuss a variety of methods by which data on gender/gender relations may be collected. In an attempt to move away from the tendency simply to count “women” and “men”, and to try to capture the relational aspects of gendered interactions, the group agreed upon a distinction between “sex-disaggregated data” and “gender-disaggregated data”. 

While we found that all sorts of data could be useful in framing certain arguments (see Street et al. 2021:  Abstract), we also discovered that a focus on categorical distinctions (“women”, “men”), even within gender-disaggregated data, made it difficult to examine how those categories came to be (Bacchi 2017). In our efforts to bring attention to the ways in which policies constituted or “made” “women” and “men”, we recommended talking about gender as a verb or gerund (gender-ing) (Bacchi and Eveline 2010: 336). The goal here is to shift attention from gender as a fixed or essential characteristic of a person, to gender-ing as an attributional process (Bacchi 2001; see previous entry 30 May 2022). We hope this creative intervention provides a politically useful way to think about “gender” and “data”.

To engage with “data”, therefore, we need to pursue St Pierre’s (2019: 10) injunction to “find concepts that reorient thinking”. Deleuze and Guattari (1988: xii) compare a concept to a brick: it can be used to build a wall or it can be thrown through a window. To shatter a few windows, it is necessary to resist the common characterization of “data” as inert research material, passively waiting to be used. Specifically, we need to find ways to draw attention to two interconnected processes: how “data” are produced, and how they are productive (constitutive), making things come to be. In the process it becomes possible to explore new ways of deploying “data”. 


Bacchi, C. 2001. Dealing with “difference”: beyond “multiple subjectivities”. In P. Nursey-Bray & C. Bacchi (Eds.), Left Directions: Is There a Third Way? Perth: University of Western Australia Press, pp. 110-122.

Bacchi, C. 2009. Analysing Policy: What’s the Problem Represented to be? Frenchs Forest: Pearson Education.

Bacchi, C. 2012. Strategic interventions and ontological politics: Research as political practice. In A. Bletsas and C. Beasley (Eds) Engaging with Carol Bacchi: Strategic Interventions and Exchanges. Adelaide: University of Adelaide Press. pp. 141-156.

Bacchi, C. 2017. Policies as Gendering Practices: Re-Viewing Categorical Distinctions. Journal of Women, Politics and Policy, 38(1): 20-41.   

Bacchi, C. and Bonham, J. 2016. Poststructural Interview Analysis: Politicizing “personhood”. In C. Bacchi and S. Goodwin, Poststructural Policy Analysis: A Guide to Practice. NY: Palgrave Macmillan. pp. 113-121.

Bacchi, C. and Eveline, J. 2010. Mainstreaming Politics: Gendering practices and feminist theory. Adelaide: University of Adelaide Press. 

Bacchi, C. and Goodwin, S. 2016. Poststructural Policy Analysis: A Guide to Practice. NY: Palgrave Macmillan.

Beer, D. 2016. How should we do the history of Big Data? Big Data & Society, January – June, 1-10. 

Bowker, G. 2013. Data Flakes: An Afterward to “Raw Data” is an Oxymoron. In In L. Gitelman and V. Jackson (Eds) “Raw data” is an oxymoron.  Cambridge, Massachusetts: MIT Press. pp. 169-171.

Bryman, A. 2006. Integrating quantitative and qualitative research: how is it done? Qualitative Research, 6(1): 97-113.

Cambrioso, A., Bourret, P., Rabeharisoa, V., and Callon, M. 2014. Big Data and the Collective Turn in Biomedicine: How Should We Analyze Post-genomic Practices? Tecnoscienza: Italian Journal of Science & Technology Studies, 5(1): 11-42.

Deleuze, G. and Guattari, F. 1988. A Thousand Plateaus: Capitalism and schizophrenia. London: Athlone Press. 

Fordyce, R. and Jethani, S. 2021. Critical data provenance as a methodology for studying how language conceals data ethics. Continuum: Journal of Media & Cultural Studies.

Garcia, N. M., López, N. and Vélez, V. N. 2018. QuantCrit: rectifying quantitative methods through critical race theory. Race Ethnicity and Education, 21(2): 149-157.   

Gillborn, D., Warmington, P. & Demack, S. 2018. QuantCrit: education, policy, “Big Data” and principles for a critical race theory of statistics. Race Ethnicity and Education, 21(2): 158-179.

Koro-Ljungberg, M. and MacLure, M. 2013. Provocations, Re-Un-Visions, Death, and Other Possibilities of “Data”. Cultural Studies, Critical Methodologies, 13(4): 219-222. 

Lather, P. 2013. Methodology-21: what do we do in the afterward? International Journal of Qualitative Studies in Education, 26(6): 634-645.

Latour, B. et al. 2012. “The whole is always smaller than its parts” – a digital test of Gabriel Tardes’ monads. The British Journal of Sociology, 63(4): 590-615.

Leonelli, S. 2014. What difference does quantity make? On the epistemology of Big Data in biology. Big Data & Society1(1): 1-11. 

Leonelli, S. 2017. Data Shadows: Knowledge, Openness, and Absence. Science, Technology, & Human Values, 42(2): 191-202. 

Mol, A. 2002. The body multiple: Ontology in medical practice. Durham and London: Duke University Press.

Sheller, M. (2014). Vital methodologies: Live methods, mobile art, and research-creation. In P. Vannini (Ed.), Non-representational methodologies: Re-envisioning research (pp. 130-145). New York, NY: Routledge. 

Springgay, S. and Truman, S. E. 2018. On the Need for Methods Beyond Proceduralism: Speculative Middles, (In) Tensions, and Response-Ability in Research. Qualitative Inquiry, 24(3): 203-214.  

St. Pierre, E. A. 2006. Scientifically based research in educa- tion: Epistemology and ethics. Adult Education Quarterly56: 239-266. 

St Pierre, E. 2011. Post Qualitative Research: The Critique and the Coming After. In N. Denzin and Y. Lincoln (eds) The Sage Handbook of Qualitative Research, 4th edn. Thousand Oaks, CA: Sage. pp. 611-25.

St. Pierre, E. A. 2016. The Empirical and the New Empiricisms. Cultural Studies, Critical Methodologies, 16(2): 111-124. 

St Pierre, E. 2019. Post Qualitative Inquiry in an Ontology of Immanence. Qualitative Inquiry 25(1): 3-16.

Street, C. et al. 2021. Do numbers speak for themselves? Exploring the use of quantitative data to measure policy ‘success’ in historical Indigenous higher education in the Northern Territory, AustraliaRace Ethnicity and Education, Tamboukou, M. and Ball, S. J. (Eds) 2003. Dangerous Encounters: Genealogy and Ethnography. New York: Peter Lang

“The data is in”: Governing through “data”

The quote in the title comes from a Radio National interview (Australia) conducted on the Breakfast program on 24 November 2021 (Yes, I was walking). The interviewee was asked about women’s excessive workload, at home and elsewhere, during the pandemic. She replied: “The data is in”, and it revealed that women did the bulk of home schooling, etc. 

Since being prompted to write about the topic of “data” and research by a participant in the recent “Kick-off” event for the planned international WPR symposium in August 2022 ( I have paid particular attention to the ways in which the term “data” appears in our conversations and in public pronouncements, by government spokespeople and researchers (see last entry 29 April 2022). As with many of the other topics I’ve broached over the past four years in this Research Hub, enquiring into the status of “data” as research material opened a Pandora’s box.

I decided to explore the issue under two broad interconnected headings: 

  1. The place of “data” in governing (this entry)
  2. The place of “data” in research (subsequent entry)

This distinction is drawn purely for heuristic purposes. From the outset I need to emphasize that how researchers “use” “data” needs to be conceived as a part of governing, as a governing practice. Drawing upon Foucault’s notion of governmentality, governing is seen to involve a broad array of agencies and groups, including professionals, experts and researchers

 On this point, it is helpful to keep in mind Annemarie Mol’s (2002: 155, emphasis in original) argument that: “Methods are not a way of opening a window on the world, but a way of interfering with it. They act, they mediate between an object and its representations”. Therefore, the production of “data”, through research, is understood to be a form of political practice that creates “realities” (see Bacchi 2012: 143). In this view, “data” operate as governmental technologies, mechanisms through which governing – understood broadly – takes place (Bacchi and Goodwin 2016: 44), as elaborated below.

With this backdrop, I advance two propositions:

first, that “data” is produced and hence it is important to reflect on the means of its production; and

second, that “data” is productive – that it produces “things” including “objects”, “subjects” and “places” (see Benozzo et al. 2013: 309). 

Readers may recognize that here I am questioning (or problematizing) “data” much in the same way I problematize “problems” in WPR – where I point out that “problems” do not simply exist out there waiting to be “solved” but that they are produced in policies as particular sorts of problem (Bacchi and Goodwin 2016: 14). I also emphasize in WPR that how “problems” are produced involves the categorization (and making “real”) of “objects”, “subjects” and “places”. Both in reference to “problems” and to “data”, therefore, the emphasis is on the production of “reality” as a performative practice (see  BACCHI KICK-OFF PRESENTATION). In poststructuralism, “a performative is that which enacts or brings about what it names” (de Goede 2006: 10)

“Data” and “problems” are linked in a second way. “Data” are generally put forward to solve “problems” – assumed to exist as clear and unquestionable states or conditions. As Valentine (2019: 365) describes, “Simply put, algorithms are mathematical processes for solving defined problems”. Hence, “data” form part of what I call the problem-solving knowledge that dominates the contemporary intellectual and policy landscape (Bacchi 2020; see also Edwards et al., 2021). The common use of “data” as “evidence” in evidence-based policy approaches confirms this link (Street et al. 2021: 1). Morozov (in Schüll 2013) labels this tendency “technological solutionism” – recasting complex social phenomena such as politics, public health, education and law enforcement as “neatly defined problems with definite, computable solutions”. As a contemporary example of “technological solutionism”, consider the former Australian Prime Minister, Scott Morrison’s, “action plan” for climate change which he characterized as reliant on “technology, not taxes” (

Generally, “data” have a taken-for-granted status as unquestioned information (Gitelman and Jackson 2013: 10).  In addition, “data” are treated as the basis of knowledge, understood as “truth”. The word “data” sits alongside allied terms such as “facts” and “evidence”. If you wish to “prove” something, you need to be able to provide back-up “data”. 

This conception of “data” lines up with a correspondence view of knowledge. “Data” are “found” in the “real world” and hence provide “knowledge” of that world – assumed to exist as fixed and inert, waiting to be known. In other words, “data” is not an innocent term. It brings with it an ontology and an epistemology, a way of thinking about “reality” and how to “interact” with “it”.

Foucauldian-influenced research offers, as an alternative to realist knowledge, a focus on how knowledges (note the plural form; see below) are produced. As argued in an earlier entry (29 Nov. 2021), in Foucauldian-influenced perspectives, “truth” is always situated. There is no universal basis for “truth”. Rather, “truth” and “knowledge” are produced in “‘local centres’ of power-knowledge” (Foucault 1990: 98). The analytic task, therefore, involves seeking out and examining the multitudes of practices – the “processes, procedures and apparatuses” (Tamboukou 1999: 202) – involved in the production of “truth” (or “truths”), rather than (simply) to uncover what is concealed. The goal becomes showing how political practice takes part in the “conditions of emergence, insertion and functioning” of “regimes of truth” (Foucault 1972: 163).

What does it mean to track how “data” are produced? What sorts of processes do we need to identify?  There are several levels at which this topic could be pursued. At one level it is possible to draw attention to where data come from (Fordyce and Jethani 2021: 3) – who asks the questions that produce data? What authority do they have?  At this level, there are expressed concerns to regulate or oversee the practices involved in the production and control of “data” in order to monitor and regulate surveillance (see Raley 2013). Padden and Öjehag-Pettersson (2021) usefully subject one such declared attempt at regulation, the EU GDPR (General Data Protection Regulation), to critical analysis using WPR. 

At a second level, “data” are produced as particular kinds of objects because they are organized in specific ways. “Data” do not speak for themselves. Through categorization and visualization, they are made to speak. Data are not just found; they are imagined (Gitelman and Jackson 2013: 3) and generated (Manovick 2020). 

Furthermore, the forms of categorization and organization that produce “data” have productive (constitutive) effects – creating “subjects”, “objects” and “places” of specific kinds. Through these effects, “data” play an active governing role, forming what governmentality scholars refer to as “technologies of rule” (Bacchi and Goodwin 2016: 44). In this view governmental instruments such as censuses, league tables and performance “data” are involved in “the conduct of conduct” (Gordon 1991: 2). 

For example, Rowse (2009) explores how the current Australian census arranges the “population” into categories (such as Indigenous and non-Indigenous) with repercussions for the sorts of political claims that can be made. In this account, numbers operate, not as a neutral, statistical register of the “real”, but as involved in shaping political possibilities. They are “integral to the problematisations that shape what is to be governed, to the programmes that seek to give effect to government, and to the unrelenting evaluation of the performance of government that characterises modern political culture” (Rose 1991: 175; see also Miller 2001).

Illustrating this point Harrington (2021) shows how the UN Secretary-General’s requirement to report on SEA (sexual exploitation and abuse) “data” shapes solutions: “The reports reflect managerial audit systems that produce a performance culture in which the goal becomes performing well for the audit”. Audit systems demand quantifiable progress in “solving” assumed “policy problems”: “Audits of not-readily quantifiable performances must contrive ways to quantify them, often with far-reaching consequences”. 

Instead of reporting on the “real”, “data” – numbers and statistics – are involved in constituting “the real”. They are involved for example in the production of an “urban/rural” dichotomy, and in the distinction between “developed” and “developing” “places” (Bacchi and Goodwin 2016: 100-104). Walters (in Tietäväinen et al. 2008: 67) describes how “Europe” has become a “domain of statistics, calculation and projections”, firming up its existence as an entity.

Fernandez (2012: 57) reminds us that the focus on statistics transforms a political issue into a technical one, described above as “technological solutionism”. She illustrates how the BLP [Below the Poverty Line] census of “poor families” used by the Indian government constitutes poverty as “lack of income”, silencing the inequitable distribution of power and access to resources. The accompanying proposal to reduce poverty by organizing the “rural poor”, specifically women, into self-help groups, creates “subjects” held to be responsible for their own welfare. 

The Programme for International Students Assessment (PISA) provides another example of how governing by numbers takes place. The Programme tabulates and compares national literacy proficiency indicators in the areas of reading, numeracy and science, indicators which translate into assessments of students, their “skills”, and labour-market performance. The Foreword to the summary of PISA 2012 results on “Creative Problem Solving” makes this connection explicit: 

“highly skilled adults are twice as likely to be employed and almost three times more likely to earn an above-median salary than poorly skilled adults.” (OECD, 2014: 3; emphasis added) 

What “skills” entail and how they are conceptualized are taken for granted, as is the computation of “success” (an above-median salary). This decision to classify students by their standardized achievement and aptitude tests “valorizes some kinds of knowledge skills and renders other kinds invisible” (Bowker and Star 2000: 5-6). As Stephen Ball (2020) describes, “the relationships of truth and power are articulated and operationalized more and more in terms of forms of performance, effects or outputs and outcomes, all expressed in the reductive form of numbers”, resulting in the “numericisation of politics” (Legg 2005: 143). 

Numbers and statistics also play a key role in the production of risk categories and statistical projections. As Dean (2010: 206) reminds us: 

“There is no such thing as risk in reality …Risk is a way, or rather a set of different ways, of ordering reality, of rendering it into a calculable form. It is a way of representing events in a certain form so they might be made governable in particular ways, with particular techniques and particular goals”. 

For example, Lancaster et al. (2020) describe how “Numbering and calculation practices have a key role in the creation, monitoring and regulation of risk populations and risk factors in public health (Castel 1991; Petersen 1997), linked to the rise of modern epidemiology and ‘surveillance medicine’ (Armstrong 1995)”. They highlight the importance of reflecting on the “forms of action” (Rowse 2009: 45; emphasis in Rowse) made possible by these calculative practices (and one might add the “forms of action” rendered irrelevant). The prominent role played by modelling in the COVID-19 pandemic provides a recent example of an intervention where such reflection is called for (Rhodes and Lancaster 2021; Rhodes et al. 2020). We need to ask: what “forms of action” have been rendered acceptable through the models produced to govern COVID-19? What possible “forms of action” go undiscussed? 

Edwards et al. (2021) show how risk categories play an increasing role in welfare governing, which they describe as an exercise in the “datafication” of citizens. People are turned into data: “identifying and categorising them to predict future behaviour, allocate resources, and determine eligibility for services and interventions” (Edwards et al. 2021: 2). As the authors explain, “The data are regularly updated, integrated and subject to application of algorithmic tools and predictive risk modelling”. One noteworthy outcome is the way in which particular families are targeted as “problematic”. Peterson and Lupton (1996) describe how this form of targeting is individualizing, “given the tendency to identify ‘risks’ in people’s lives while leaving them responsible to reshape their lives to meet those risks”. 

Statistical risk assessments also function prominently in the criminal justice system. For example, Padden and Öjehag-Pettersson (2021) highlight the role of algorithmic profiling 

“to detect welfare and tax fraud, assess the likely truthfulness of police complaints, assist in sentencing decisions, and make predictions or trigger ‘risk alerts’ in child welfare, policing, eldercare and psychiatric services (Dencik et al. 2018; AlgorithmWatch 2019)”. 

“Predictive policing” algorithms are now being used in law enforcement to determine areas where crime is likely to occur. “Re-offending algorithms” are also being used as a part of sentencing. Elliott Smith (2019: 8-10) reminds us that such algorithms, which necessarily require simplification in order to work, are reductive and reflect prevailing prejudices, “making bigots of us all” (see Street et al. 2021: 159). For example, Edwards et al. (2021: 15) show how the predictive risk modelling used in child protection obscures the in-built equation of socio-economic disadvantage with risk, building in discrimination against the poor. 

Importantly, Gitelman and Jackson (2013: 8) point out that “data aren’t only or always numerical”. However, while they do not always exist in number, data are treated as particulate – in the form of separate particles. For example, “qualitative data” and “interview data” involve attention to specific bits of “information”, raising the suggestion that references to “data” in such contexts may well be metaphorical (pursued in next entry) (Gitelman and Jackson 2013: 10). 

Because data are particulate, data practices are necessarily aggregative – “They [data] are collected in assortments of individual, homologous data entries and are accumulated into larger or smaller data sets” (Gitelman and Jackson 2013: 8; emphasis in original). It is these practices of organization, classification and deployment that need to be tracked. The goal, according to Bowker and Star (2000: 4), is to identify the origins and consequences of a range of social categories and practices. 

You may have noticed that throughout this entry I have used “data” as a plural noun – referring for example to “data are” rather than to “data is” (unless I am quoting someone who uses the singular form as in the title).  I apologize to those of you who find grammar uninteresting and hope you may come to see that there is a great deal at stake in whether “data” is treated as “it” or as “they”. I should caution that adopting “data” as a plural is not always easy to implement, given the common singular usage. I had to go back to correct this entry in several places where I had slipped inadvertently into talking about data as “it”.

There appear to be two camps of thought on the topic. The Oxford English Dictionary accepts that the concept of “data” is generally not treated as a plural but as a mass noun (like “information”), an “uncountable noun” that takes a singular verb (i.e., data is) ( By contrast, the Publication Guidelines for the American Medical Association state that the singular noun is “datum”, and the plural is “data”, the latter necessitating a plural verb (i.e. data are) (  

I prefer and promote the second plural option on the grounds that treating “data” as a singular item, a “mass noun”, produces “it” as a “thing”, with some sort of fixed parameters. In the process the practices involved in “its” production and organization go unobserved and unanalysed. Using “data” in the plural provides a simple way to ensure that how “data” are produced becomes a necessary feature of one’s analysis. Poststructuralists use a similar stratagem in references to knowledgesrather than to knowledge, which is commonly characterized as a “mass noun”.

Clearly, “mass nouns” are not innocent. They assume a specific epistemology and have political effects. They reflect a trend among users of the English language to “focus more on categories and classifications which define a thing and fix its nature for all time” with less concern for “processes, movement and change” (Hoagland 1988: 224). A poststructural approach to concepts and categories aims to return attention to those processes.   

Other attempts to highlight the fluid and constructed character of “data” include references to “datafication” (see above regarding “datafication of citizens”) and “datafying”. However, these terms have already been co-opted by data analysis companies.  “Datafication” is now commonly adopted to refer to “the collective tools, technologies and processes used to transform an organization to a data-driven enterprise”( In this understanding an organization that implements datafication is said to be “datafied” (

Elsewhere I have written about the possible use of gerunds (turning a noun into a verb form by adding “ing”) as a poststructural conceptual strategy to direct attention to the ongoing formation of “things” deemed to be fixed in place and/or time. The concepts of “gender-ing” and “border-ing” are put forward as a means of directing attention to the practices involved in the becoming of “things”, rather than simply accepting them as unchanging states of being (Bacchi 2017; Bacchi and Goodwin 2016: 100). For data, then, we might try referring to “data-ing” – though I suspect that such an awkward term is unlikely to become popular.  

Clearly, then, researchers face many dilemmas in relation to “data”, including the rather basic task of how to refer to data without inadvertently producing “it” as a politically neutral singularity. More broadly, returning to the question/comment in the “Kick-off” event, there is an ongoing presumption in mainstream social science studies that research arguments will be “backed up” by data. At the same time and in dramatic contrast, recent debates around the need for “post-qualitative” research put into question the use of all forms of “humanist” research (St Pierre 2013: 226), including research that relies on data. How are researchers to negotiate this minefield? I reflect on this topic in the next entry.  


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Red alerts and political thinking: Preliminary thoughts on “data”

Every day (unless it is ferociously stormy, which happens seldom in Adelaide) I take a 45-minute morning walk and listen to the Australian public broadcaster, Radio National. I am a creature of habit! This morning (Dec 3, 2021) two items caught my attention.  They both mentioned “data”, and this is the topic I’ve been thinking about. I was prompted to reflect on “data” by a question/comment in the “Kick-off” event for the scheduled International WPR Symposium in Karlstad, August 2022 ( 

The researcher noted that she had been challenged to explain how she used “data” given that WPR is an interpretive approach. This question of the relationship between “data” and research methods is highly topical and will be pursued in subsequent entries. 

Returning to my morning walk and the radio program, in one item, a Melbourne academic, Dr Lauren Rosewarne, commented on the Federal Government’s proposed “anti-trolling” legislation. Under the proposed legislation, the laws would require social media companies to collect personal details of current and new users, and allow courts to access the identity of users to launch defamation cases. 

Dr Rosewarne raised several concerns. The proposed legislation, she noted, was complaint-based, and hence relied upon individuals having the resources to pursue complaints. She also asked if the listeners wanted social media companies to hold “data” on them. At one point she made this additional point: “The solution doesn’t seem to match the policy problem from my perspective”. My ears pricked up at the mention of “problems” (trolling) and “solutions”. Those familiar with WPR will be able to see its thinking at work in the analysis produced. 

Dr Rosewarne pointed out that the “postulated solution” (the policy) produced the “problem” as defamation. She elaborated on the inadequacy of this approach. Defamation of character, she explained, which politicians assume characterizes abuse online, does not cover the forms of harassment trolling entails. Things are missing from this analysis (WPR, Question 4), with severe limitations for the usefulness of the intervention (WPR, Question 5; see Chart below.).

I would like to suggest that the terms “problems” and “solutions” serve as “red alerts”, stopping us in our tracks and impelling us to apply WPR thinking.  The hope is that such a strategy produces a useful form of political thinking. 

The second item that caught my attention, reported in the Radio National News on 3 Dec 2021, was on emissions measurement (I was still walking!). It was based on a Dutch study which claimed that the Australian government was underreporting levels of emissions (

The headline, indicated in the link, read: “New data suggests Australia could be underreporting …”. One point jumped out in the summary of the Dutch report – it seems the Australian government received its emissions data from the oil companies. So “data” proved useful in questioning “data”. The point resonated with some of the reading I have been doing around “data” – that they [note the plural usage; explained in next Research Hub entry] can be useful to some researchers and that, at the same time, “data” are not simply inert “facts” but that they are produced in social processes. These are themes I intend to pursue in subsequent entries.

The point of this very brief interlude is to suggest that I was sensitized to the political relevance of “data” by my recent reading and by the appearance of the issue as a topic of concern at the “Kick-off” event. For me, “data” is now a “red alert” term. I now notice the term “data”, whereas previously it had operated as a taken-for-granted concept that escaped attention. I wonder if readers might like to share with us some other “red alert” terms. I could post them in a subsequent entry. I would also love examples where WPR became useful for you in your daily encounters with the news or some political announcement, where it prompted what I would like to call political thinking

What’s the Problem Represented to be? (WPR) approach to policy analysis 

Question 1: What’s the problem (e.g., of “gender inequality”, “drug use/abuse”, “economic development”, “global warming”, “childhood obesity”, “irregular migration”, etc.) represented to be in a specific policy or policies? 

Question 2: What deep-seated presuppositions or assumptions underlie this representation of the “problem” (problem representation)? 

Question 3: How has this representation of the “problem” come about? 

Question 4: What is left unproblematic in this problem representation? Where are the silences? Can the “problem” be conceptualized differently? 

Question 5: What effects (discursive, subjectification, lived) are produced by this representation of the “problem”?
Question 6: How and where has this representation of the “problem” been produced, disseminated and defended? How has it been and/or how can it be disrupted and replaced? 

Step 7: Apply this list of questions to your own problem representations.

C. Bacchi and S. Goodwin (2016) Poststructural Policy Analysis: A Guide to Practice. NY: Palgrave Macmillan, p. 20. 

Can WPR contribute to “solution-construction”? Should it do so? Part 3

See 30 Dec. 2021 for Part 1 and 30 Jan. 2022 for Part 2.

In 1999 I wrote the first book, entitled: Women, Policy and Politics: The Construction of Policy Problems (London: Sage), that explored the propositions that became WPR (a “What’s the Problem Represented to be?” approach). in that book I introduced an approach I referred to as: “What’s the problem?”, with a parenthetical reference: “(represented to be)”. I realized shortly after publication that the abbreviated question – “What’s the problem?” – was misleading, since people tended to interpret it to mean that the goal was finding the real problem. My friend and colleague, Angie Bletsas, suggested the acronym WPR to ensure that those who adopted the analytic strategy I was developing kept the focus on how “problems” were represented in policy proposals. 

The subtitle of the 1999 book – “The construction of policy problems” – signals my engagement at that time with social construction theory. Reflecting a constructionist perspective, I often referred to competing interpretations of “problems” (e.g., see pages 9-10). Alongside these references, I developed the position that I went on to endorse in later work (Bacchi 2009; Bacchi and Goodwin 2016) – that policies “enact” or produce “problems” as particular sorts of problems: “every policy proposal contains within it an explicit or implicit diagnosis of the problem, which I call its problem representation” (Bacchi 1999: 1).

It is important to recognize that researchers can modify their theoretical positions as they encounter fresh perspectives. Over the last twenty years, I have worked more closely with the performative approach as developed in the work of John Law (2004; Law and Urry 2005) and Annemarie Mol (1999; 2002). I now regret the way in which the language of “interpretation” crept into the 1999 analysis. Indeed, I have struggled ever since Women, Policy and Politics to distinguish WPR frominterpretive approaches to policy analysis (Bacchi 2015). While some researchers express the view that it is quite acceptable to use the label “interpretive” in a broad sense that could encompass WPR (Barbehon 2020: 143 fn 5), I draw a contrast between the focus in interpretivism on people’s understandings of issues and a WPR analysis of the implicit problem representations in governmental problematizations. The point in drawing this contrast is to emphasize that WPR is not geared to study what goes on in people’s heads but directs attention to mechanisms of rule and how they function. 

In Women, Policy and Politics, then, I was experimenting with a particular way of thinking that has since been elaborated and clarified. The 1999 volume represents the initial steps in an intellectual journey that remains ongoing. In this entry I revisit Women, Policy and Politics to consider how I dealt with the question of “solutions”, to see what might be of value in my first thoughts on the matter and to indicate what I would now wish to revise. 

The question of “solutions” is dealt with most directly in the chapter on pay equity (Bacchi 1999: Chapter 4). This chapter offers, I believe, some tentative guidance on how to use WPR to think differently about reform efforts. I use the chapter on pay equity to introduce Part 2 of Women, Policy and Politics, which deals with the major legislative attempts to produce what was described as “women’s equality”. Alongside pay equity, I examine education reform, childcare policy, affirmative action and anti-discrimination, abortion reform, domestic violence and sexual harassment reform. 

In the chapter on pay equity I start from specific proposals (as in my later publications on WPR; Bacchi 2009; Bacchi and Goodwin 2016). I then show how each proposed reform represented the “problem” of pay inequity quite differently. The topic of pay equity is complicated and I can recall being daunted by the technicalities in specific attempts to establish fairer pay scales for women. I recommend those interested in the topic to read all of Chapter 4 (Bacchi 1999, pp. 72-92). 

Put briefly, I distinguish among several ways of “framing” the “problem” of pay inequity: equal pay for equal work, equal pay for work of equal value (otherwise known as “comparable worth”) and wage solidarity. In “equal pay for equal work” the target of critique is employer discrimination. In comparable worth approaches, the “problem” is represented to be the wage gap between women’s and men’s wages due to women’s location in specific undervalued jobs (e.g., the “caring” professions). In wage solidarity, the proposal to raise women’s wages by raising wages across the board creates the “problem” as worker exploitation.

In close approximation to my present position, I note that “a focus on proposals” permits “the elaboration of problem representations which in turn provides insights into the kinds of claims being made and the effects these claims tend to produce” (Bacchi 1999: 72). The “elaboration of problem representations” involves the identification of deep-seated presuppositions (Question 2 in WPR; Bacchi and Goodwin 2016: 20). The focus on effects points to the need to consider how specific problem representations affect people’s lives. In later work this focus becomes Question 5, which insists it is possible to “assess” problem representations in terms of their discursive, subjectification and lived effects (Bacchi and Goodwin 2016: 20). 

The insistence that “assessment” of problem representations is possible raises the question about the purpose of this intervention. Surely, it could be argued, the point of assessment is to assist in the determination of which reforms are most “useful”. In Women, Policy and Politics (Bacchi 1999:90) I describe the goal of assessment as encouraging “reformers to make proposals which reduce or obviate some of the regressive effects which have been identified in some problem representations”. 

I would now describe this comment as insufficiently critical on my part. I would no longer refer to “regressive effects” as if it is clear and transparent what such effects look like. For similar reasons, I am unhappy with my claim regarding pay equity that it is possible to work “carefully within constraints to frame problems in ways that maximize gains and minimize losses” (Bacchi 1999: 91), as if “gains” and “losses” can easily be identified. Rather, I would now insist that any such assessment needs to remain open to discussion and contestation. 

At the same time, I think it is possible to make the case that the kind of interrogation of policy proposals encouraged by WPR assists reformers/activists “in pinpointing what it is about particular proposals that disturbs us” (Bacchi 1999: 90). I use the remainder of this entry to explain the grounds for this argument, in the process clarifying the ways in which WPR can assist at the coalface of legislative reform. 

My example is Burton et al.’s (1987: 90-94) pay equity intervention and how it produced the “problem”. The Burton intervention avoided the tendency to speak about women’s “caring” work and “caring skills” in job evaluation, concerned that such a designation tended to essentialize women as carers. Instead, it offered a reworking of the category “Human Relations”, highlighting how current practices tended to value responsibility for people if those practices involved “pursuit of organisational objectives” but not if they involved “contributing to the quality of working relationships in other ways”. So, “working through and down the hierarchy” is valued over working “laterally and up”. This careful reframing of the “problem” problematizes hierarchy at the same time as it targets the need to rethink the roles played by those designated “women” and “men” in organizations. 

In this instance applying WPR to specific pay equity initiatives encourages reflection on factors (here, job hierarchy) that may not be identified as problematic in conventional pay equity evaluations. In other words, it serves to broaden the parameters of what ought to be considered relevant to a specific area of reform. 

Similarly, applying WPR to pay equity strategies highlights their reliance on a conventional understanding of “skills”, a category that requires critical analysis. As Bastalich (2002) argues, the felt need to justify women’s “skills” as “learned”, as opposed to “natural”, buys into a particular version of human beings as “skill-acquiring” animals. WPR encourages us to ask where this concept comes from and how our assumptions about its existence shape our thinking and reform proposals. Campaigns for “skills” recognition can no longer be treated as obviously appropriate and worthwhile; rather, reformers are challenged to reflect on the effects of the categories of thought they adopt. 

Women, Policy and Politics is filled with examples that highlight the need for feminists to question their own underlying premises. In fact, it takes its inspiration from the numerous feminist interventions that have undertaken precisely this task (Bacchi 1999: 11). In this sense, Women, Policy and Politics (1999)  can be seen to be an exercise in feminist self-problematization. I offer one more example of this dynamic – the introduction by the Canadian Immigration and Refugee Board of guidelines on gender-related persecution (Bacchi 1999: 177-178). The Guidelines cover two types of cases: first, “women fleeing severely abusive spouses, who can show that their countries of origin are unwilling or unable to protect them”, and second, “women living in countries where they encounter severe state-sanctioned discrimination” (Immigration and Refugee Board 1993, cited in Razack 1995: 47). 

Razack (1995: 47) notes that the Guidelines are “the culmination of intensive lobbying by women’s groups and various Canadian and international efforts to address the issue of domestic violence as a form of persecution”. At the same time, she is concerned about some of the effects that flow from the way in which the “problem” tends to be represented. She notes (1995: 46, 49), for example, that refugee hearings are always “profoundly racialized” events in which the “outwardly compassionate process of granting asylum” creates “First World countries as benefactors”, while the people of the Third World are created as “supplicants asking to be relieved of the disorder of their world and to be admitted to the rational calm of ours”. This representation of the “problem” ignores and belies the role of the First World in creating, through economic exploitation, the circumstances of the distress suffered by refugees.

Now, importantly, Razack does not argue that feminist reformers ought to stop using “gender persecution” to advance the cause of women refugees. But she does want feminist reformers to “explore ways in which we might talk about women and the violence they experience” that acknowledge the operation of power relations between First and Third Worlds. She suggests that a way forward here is to produce gender persecution legislation “as one element of a multi-pronged strategy in which the goal would be to change social structures that propel men to be violent and condone their excesses” (Razack 1995: 71). WPR, I suggest, provides assistance in thinking through precisely what this task entails. 

In a WPR approach to policy development, context plays a critical part. Returning to the example of pay equity, there is a hesitancy to make sweeping generalizations about reform approaches – e.g., preferring wage solidarity over comparable worth (or vice versa) in every instance. Rather, it encourages a sensitivity to specific contexts where particular forms of engagement may or may not be possible. For example, Acker (1989: 196) shows that, in Oregon in the 1980s, constructing the problem as poverty relief (wage solidarity) proved to be a more successful reform strategy than equity agreements which, given the specific labor relations context, appeared to set worker against worker. In tune with Foucault’s own “version of emancipation”, universals are replaced with “specific transformations” that minimize domination (Moss 1998: 9). 

Lest this example seem to herald a pragmatic approach to policy development, I question the pragmatist’s claim that skepticism (questioning or problematizing) “forms an obstacle to a creative handling of problems”: “Anyone who puts everything up for discussion will simply have no time left for the real problems of the moment” (Keulartz 2002: 15; emphasis added). It is of course the very presumption in these statements that “real problems” exist as self-evident “things” or conditions that WPR sets out to challenge. 

The objective in WPR is to tease out the implications of different problem representations. It sharpens an awareness of the effects of the frameworks we adopt and encourages us to find proposals that “diminish effects we want to discourage” (Bacchi 1999: 90). Importantly, the question of what ought to be discouraged remains an open question – one that needs to be on the table – not one that is assumed beforehand.  


Acker, J. 1989. Doing Comparable Worth: Gender, Class and Pay Equity.Philadelphia: Temple University Press.

Bacchi, C. 1999. Women, Policy and Politics: The Construction of Policy Problems. London: Sage.

Bacchi, C. 2009. Analysing Policy: What’s the Problem Represented to be? Frenchs Forest: Pearson Education.

Bacchi, C. 2015. The turn to problematization: Political implications of contrasting interpretive and poststructural adaptations. Open Journal of Political Science, 5, 1–12.

Bacchi, C. and Goodwin, S. 2016. Poststructural Policy Analysis: A guide to practice.  NY: Palgrave Macmillan.

Barbehon, M. 2020. Reclaiming constructivism: towards an interpretive reading of the “Social Construction Framework”. Policy Sciences, 53: 139-160.

Bastalich, W. 2002. Politicising the productive: subjectivity, feminist labour thought and Foucault. PhD thesis, University of Adelaide, Departments of Politics and Social Inquiry. 

Burton, C., with Hag, R. and Thompson, G. 1987. Women’s Worth: Pay Equity and Job Evaluation in Australia. Canberra: Australian Government Publishing Service. 

Hacking, I. 2007. On Not Being a Pragmatist. In C. J. Misak (ed.) New Pragmatists. Oxford: Oxford University Press.

Immigration and Refugee Board 1993. Guidelines Issued by the Chairperson Pursuant to Section 65(3) of the Immigration Act. Immigration and Refugee Board. 

Keulartz, J., Korthals, M., Schermer, M. and Swierstra, T. 2002). Ethics in a Technological Culture: A Proposal for a Pragmatist Approach. In J. Keulartz et al, (eds) Pragmatist Ethics for a Technological Culture. Dordrecht: Springer-Science+Business Media.

Law, J. 2004. After method: Mess in social science research. London and New York: Routledge. 

Law, J. and Urry, J. 2005. Enacting the social. Economy and Society, 33(3): 390-410.

Mol, A. 1999. Ontological politics: A word and some questions. In J. Law & J. Hassard (Eds.), Actor network theory and after. Oxford: Blackwell. 

Mol, A. 2002. The body multiple: Ontology in medical practice. Durham and London: Duke University Press.

Moss, J. (1998). Introduction: The later Foucault. In J. Moss (Ed.), The later Foucault: Politics and philosophy. London: Sage. Razack, S. 1995. Domestic Violence as Gender Persecution: Policing the Borders of Nation, Race and Gender. Canadian Journal of Women and the Law, 8: 45-88.

“Becoming More Mortal”: governing through “risk”, “vulnerability” and “underlying health conditions”

“Becoming More Mortal”:  governing through “risk”, “vulnerability” and “underlying health conditions”

I apologize for breaking the flow of promised Research Hub entries, but such is the nature of the times. I felt compelled to say something about modes of governing COVID-19 that are currently (Jan – Feb 2022) being practised. Specifically, I wish to reflect on dominant people categories and their governing effects, including lived and subjectification effects (see WPR question 5; Bacchi and Goodwin 2016: 20). The categories I wish to target are interconnected: “underlying health conditions”, “at-risk populations”, “vulnerable groups”, “hospitalization [or death] with COVID as distinct from hospitalization [or death] from COVID”. I intend to consider these issues alongside a narrative of my own experiences to indicate the power and influence of governing categories.


I have a chronic health condition. It leaves me immunocompromised (immunosuppressed). Notice how I’ve already taken on two categories, and I have only just begun! 

Allow me to digress briefly. In my 2003 memoir, entitled Fear of Food: A Diary of Mothering (Spinifex Press), I reflected on the repercussions of being classified as an “elderly primigravida” when I became pregnant at age forty-four: 

“Being of a certain age for your first child means that you are automatically considered a high-risk pregnancy. … I tried to deny the implications of being labelled ‘high risk’, but we shouldn’t ignore the impact of medical diagnoses on our psyche. In fact, you could say that being called ‘high risk’ was not a way to make you feel relaxed about your pregnancy” (Bacchi 2003: 3). 

This sensitivity to the impact of governing categories was reflected in my 1996 book, The Politics of Affirmative Action, which developed the notion of “category politics”. This concept (which germinated in my pre-Foucauldian days) incorporates the political uses of both conceptual and identity categories. 

With this background, unsurprisingly, I pay close attention to the categories of analysis deployed in responses to COVID-19. Hence, I began to dwell on a category that was receiving almost daily mention in the numerous press conferences by the Prime Minister, State Premiers, Health Ministers and Public Health Officers in Australia. Allow me to note in passing the impact of the pandemic on the status and influence of public health, at least in certain settings, indicated in Australia and overseas in the “rock star” status accorded certain Public Health Officers (see Anders Tegnell in Sweden,

The category that drew my attention and my ire was “underlying health conditions”. It started to appear in daily reports of deaths “associated with COVID-19” in November 2021. With my chronic health condition, I recognized myself in the category and wondered about the possible objective in its use. Perhaps the intent was to make “regular” people feel less worried about their possible sickness and death (Laterza & Romer 2020). Or, just perhaps, the category diverted attention from COVID-19 itself and its (mis)management to “underlying” conditions that would probably/possibly do you in. 

And then serendipity!  I was reading Louise Erdrich’s wonderful novel The Sentence at the time of these increasingly disturbed concerns about my chronic condition and COVID-19. She writes:

“The Reports kept saying that those who died had underlying health issues. That was probably supposed to reassure some people – the super-healthy, the vibrant, the young. A pandemic is supposed to blow through distinctions and level all before it. This one did the opposite. Some of us instantly became more mortal. We began to keep mental lists. One morning we started figuring the odds.”

“You get an automatic point for being a woman”, said Pollux, “plus ten years younger. That’s two points.”

“I think we both get a point for having blood type O. I’ve heard type A is more susceptible”. 

“Really? I’m not sure. I’d question that”. 

“We have to subtract those points anyway for being a teeny bit overweight”. 

“Okay, let’s cancel those two factors out”.


“I lose a point for having asthma”, said Pollux. “You get a point for not having it”. 

“Although now they’re saying it might not make a difference. But I’ll give you the point”. (Erdrich 2021: 183-184; emphasis added).

But that is me, I decided! Was I keeping score? Not intentionally, but perhaps under the radar I thought – you may have a chronic condition but at least you are not obese, and you don’t have sleep apnoea. Queensland’s Public Health Officer, Dr. Kerry Chant, recently reported that a coroner’s review of deaths of 28 people under the age of 65 infected with  COVID-19 identified both obesity and sleep apnoea as “related” conditions (

It was time to put on my Foucauldian hat before I threw up my hands in despair and surrendered completely to the practices of categorization dominating public debate.

Governing through risk technologies

Dr. Chant drew a connection between “underlying health conditions” and “risk”: “… those who are elderly and those that have underlying health conditions are most at risk of severe disease, hospitalization and death” (

This reference to “risk” is an uncontroversial statement in public health terms. However, that does not mean that it is uncontroversial.

A great deal has been written about “risk”, “risk categories” and “risk technologies” by critical scholars, including those interested in governmentality. The notion of “risk technology”, associated with those researchers, highlights the role of “risk” categories as mechanisms of governing. In a subsequent entry on “data”, I illustrate this point with references to the role of risk categories in welfare governing, in statistical risk assessments in criminal justice, and in predictive risk modelling. 

The governmentality scholar, Mitchell Dean, provides us with a way to think about “risk” and its role as a governing technology. He reminds us: 

“There is no such thing as risk in reality …Risk is a way, or rather a set of different ways, of ordering reality, of rendering it into a calculable form. It is a way of representing events in a certain form so they might be made governable in particular ways, with particular techniques and particular goals”. (Dean 1999: 177)

To come to understand how “risk” functions as a governing mechanism, Dean advises that researchers tease out “the forms of knowledge that make it thinkable”, and “the political rationalities and programs that deploy it” (Dean 1999: 178). 

This approach to “risk” indicates how a WPR analysis can be useful in this context. Instead of generalizing about the notion of “risk” as if it has a set and obvious meaning, we need to identify the knowledges relied upon to give it meaning, and to examine how the concept represents the “problem” in specific circumstances. 

How then does the creation of “the elderly” and those with “underlying health conditions” as “at risk” of disease and death shape governing practices? It could, of course, translate into increased resource allocation or more targeted health services. Or, it could serve to “explain” and explain away higher than usual death rates (see

Governments at both the federal and state levels in Australia decided that the practices of relaxing restrictions and opening borders (international and state) in December 2021 needed to be accompanied by a shift in focus from COVID-19 case numbers to the numbers of those hospitalized and of deaths. As the numbers in hospitals rose, Prime Minister Morrison sought a new definition for hospital cases, distinguishing those admitted due to Covid from those admitted for “unrelated reasons” and testing “positive during routine inspections” (Day 2022). As the death toll rose, it became important to offer plausible explanations for this rise that did not draw attention to poor pandemic management practices or to COVID-19 itself, as these deaths could be anticipated (Herrick 2020). “Underlying health conditions” proved to be a useful public health intervention in this regard.

A J P Morgan economist defended the practice of recording the deaths of people who died with COVID-19 separate from those people who died because of COVID-19 – a difficult distinction to make (Trabsky 2020) – lowering the CFR (case fatality rate) in Denmark from 0.045 per cent to 0.027 per cent ( In Australia Morrison continues to defend the distinction between “passing away with Covid” and “passing away because of Covid” (Daily Mail 16 Feb 2022;

I am not suggesting deliberate manipulation in this usage. Rather, I wish to draw attention to the way in which public health knowledge served to make a case about the need to “open up”, a case that would resonate with many in the general population – since we have been told for decades that if we don’t keep the weight off and exercise regularly, we will develop “underlying health conditions”. 

Governing through vulnerability 

At the same time, targeted groups – and these usually include the elderly, people with disabilities, Indigenous peoples, and those with chronic health conditions – are frequently described as “vulnerable”. Indeed, the main riposte to perceived government mismanagement of the pandemic, at least in Australia, is that our “most vulnerable citizens” have been ignored. In this situation it becomes difficult to suggest the need to rethink the category of “vulnerability”, but I believe it is necessary to do so. 

In a previous entry (Research Hub 31 Aug 2020) I described how, in work with Chris Beasley, we challenged a dominant conceptualization in Australian public policy that sets “vulnerable” bodies against other healthy bodies. Vulnerable bodies are seen to reflect a view that people are controlled by their biology, that they are (so to speak) at the mercy of their bodies (Bacchi and Beasley 2002). This view is contrasted to a preferred default position, in which perceived autonomous rational actors keep their bodies in line or “under control”.

There are downsides to both positions – the citizens who are deemed to have control over their bodies become “responsibilized”, and are held responsible for their health outcomes. Petersen and Lupton (1996) argue that public health constructions of risk are premised on the expectation that individuals will govern their own risk-taking practices (see also Nettleton 1997). This perspective is currently endorsed in the federal government’s refrain that, in relation to the pandemic, it is time for Australians to demonstrate “self-responsibility” (SBS News 21 Dec. 2021; (on this theme in Sweden see NyGren & Olofsson 2020). Australian government websites offer guidance on “what you can do to reduce your risk or that of someone you care for.

On the other hand, those characterized as controlled by their bodies – i.e., the “vulnerable” – are constituted as lesser citizens (Bacchi and Beasley 2002). In these cases, Beasley and I highlight the often, inadvertent acceptance of a hierarchical relationship between those who can care versus those who need care. We further characterize this relationship as displaying “the residues of noblesse oblige”, effectively denying the socio-political relations that constitute this hierarchy (Beasley and Bacchi 2007: 293). 

It is important also to note that health promotion programs that target “at risk” populations can be stigmatizing (Bacchi and Goodwin 2016: 74), singling them out as wanting or weak. Shani (2020) adds that the fact that the most “vulnerable” people are also those of retirement age is significant “for they are deemed surplus to the requirements of a functioning capitalist economy”. They are “disposable” populations (Duffield 2007), expendable, exerting “additional pressures” on government budgets (Australian Government 2013). 

At some level this willingness to accept the deaths of specific groups of elderly people, Indigenous peoples, those with disabilities and those with co-morbidities raises disturbing reminders of eugenic theories and the notion of survival of the fittest (Laterza & Romer 2020). Connections have been drawn between the defence of “herd immunity” as a pandemic strategy and Malthusian population theories (Malinverni 2020). “The ‘herd’ will survive, but for that to happen, other ‘weaker’ members of society need to be sacrificed” (Laterza & Romer 2020). At the same time the “herd” will build up its immunity to SARS viruses. 

I don’t have space here to sort through the competing ideas about the role of heredity in evolution in the 19th and 20th centuries (Bacchi 1980), or the distinctions between “negative” eugenics, with its endorsement of compulsory sterilization of the “unfit”, and “positive” eugenics, looking to environmental and hygienic reforms to improve “the race” (Dean 2015: 25). Rather, I’m suggesting that it is useful to take a broader perspective and to think about how policy decisions create the “problem” of “population” – here in terms of “the people” versus “the expendables”. 

Of course, the language of “herd immunity” is less popular today, at least in Australia. Rather, there are suggestions that we should  “let it rip” or, more commonly, that we have to learn to “live with the virus” (

 In any event, the lived effects for members of the disability community, Indigenous peoples, and residents in aged care homes frequently involve severe illness and, all too often, death. 

Ways forward

Beasley and I (2007) suggested that there is a need to develop new frameworks of meaning to rethink the ways in which governmental practices conceptualize bodies. To this end we offer the concept of “social flesh” to bypass the constructed dichotomy between those characterized as controlling their bodies and those deemed to be controlled by their bodies, between the “marketable” and the “disposable” (Shani 2012). 

Our hope is that “social flesh” might serve to disrupt the current dominant neoliberal ethic that privileges autonomous, rational actors who are held responsible for their lives and health, and to highlight the unequal burden of infectious diseases (Research Hub 31 July 2020). “Social flesh” does this by drawing attention to shared embodied reliance, mutual reliance, of people across the globe on social space, infrastructure and resources (Beasley and Bacchi 2007).  

The call by Dr Tedros Adhanom Ghebreyesus, Director-General, World Health Organization, to get “all countries to work together to reach the global target of vaccinating 70% of people in all countries by the middle of 2022” indicates recognition of that embodied reliance. In the place of “narrow nationalism and vaccine hoarding by some countries”, he argues, there is a need to negotiate “a global pandemic accord to strengthen the governance, financing, and systems and tools the world needs to prevent, prepare for, detect and respond rapidly to epidemics and pandemics”.

The goal, put simply, is for all of us to become more mortal rather than scapegoating those with “underlying health conditions”. 


Australian Government 2013. An Ageing Australia: Preparing for the Future. Productivity Commission. Available at:

Bacchi, C. 1980. The nature-nurture debate in Australia, 1900-1914. Historical Studies, 199-212.

Bacchi, C. 1996. The Politics of Affirmative Action: “Women”, Equality and Category Politics. London: Sage. 

Bacchi, C. 2003. Fear of Food: A Diary of Mothering. Spinifex Press. 

Bacchi, C. and Beasley, C. 2002. Citizen bodies: Is embodied citizenship a contradiction in terms? Critical Social Policy, 22(2): 324-52. 

Bacchi, C. and Goodwin, S. 2016. Poststructural Policy Analysis: A Guide to Practice. NY: Palgrave Macmillan.

Beasley, C. & Bacchi, C. 2007. Envisaging a new politics for an ethical future: Beyond trust, care and generosity —towards and ethic of “social flesh”. Feminist Theory, 8(3): 279-298. 

Day, O. 2022. Scott Morrison pushes to reclassify Covid hospital admissions. The Daily Mail, 4 January. Available at: < › news › article-10365467>

Dean, M. 2010. Governmentality: Power and Rule in Modern Society. Second ed. New York: Sage.

Dean, M. 2015. The Malthus Effect: population and the liberal government of life. Economy and Society, 44(1): 18-39.

Duffield, Mark (2007) Development, Security and Unending War: Governing the World of Peoples, Cambridge: Polity.  

Erdlich, L. 2021. The Sentence. Harper.

Herrick, C. 2020. “Syndemics of COVID-19 and ‘pre-existing conditions’”. Somatosphere.

Laterza, V. & Romer, L. P. 2020. Coronavirus, herd immunity and the eugenics of the market. Aljazeera. Available at:

Malinverni, C. 2020. COVID-19, Scientific Arguments, Denialism, Eugenics, and the Construction of the Antisocial Distancing Discourse in Brazil. Frontiers in Communication, 4 November. Available at:

Nettleton, S. 1997. Governing the risky self: How to become healthy, wealthy and wise’. In A. Petersen and R. Bunton (Eds) Foucault, Health and Medicine. London: Routledge. 

Nygren, K. G. & Olofsson, A. 2020. Managing the COVID-19 pandemic through individual responsibility: the consequences of a world risk society and enhanced ethopolitics”. Journal of Risk Research, 23(7-8).

Petersen, A. & Lupton, D. 1996. The new public health: Health and self in the age of risk. London: Sage.

Shani, G. 2012. Empowering the disposable? biopolitics, race and human development. Development Dialogue. Available at:

Shani, G. 2020. Securitizing “Bare Life”? Human Security and Coronavirus. E-International Relations. Available at:

Trabsky, M. 2020. “Died from” or “died with” COVID-19? We need a transparent approach to counting coronavirus deaths. The Conversation, 9 September. 

My sincere thanks to Anne Wilson, Jennifer Bonham and Angie Bletsas for comments on an earlier draft.