My new book: The Quantified Self

My new book The Quantified Self: A Sociology of Self-Tracking is due out with Polity Press this April. The publishers are offering a 20% discount for six months (from 18 January 2016 to 31 July 2016) if it is ordered via their website. Please use the code PY703 when you order to receive the discount.

Here is a PDF of the Introduction: Lupton 2016 Introduction to The Quantified Self.

Table of Contents

Acknowledgements

Introduction

1          ‘Know Thyself’: Self-tracking Practices and Technologies

2          ‘New Hybrid Beings’: Theoretical Perspectives

3          ‘An Optimal Human Being’: the Body and Self in Self-Tracking Cultures

4          ‘You are Your Data’: Personal Data Meanings, Practices and Materialisations

5          ‘Data’s Capacity for Betrayal’: Personal Data Politics

Conclusion

References

Index

 

POLITY-Lupton-Quantified Self Visuals-AUG24-3 (1)

 

My 2015 publications

Here are my publications that came out in 2015.

Book

  • Lupton, D. (2015) Digital Sociology. London: Routledge.

Book chapters

  • Lupton, D. (2015) Digital sociology. In Germov, J. and Poole, M. (eds), Public Sociology: An Introduction to Australian Society, 3rd St Leonards: Allen & Unwin.
  • Lupton, D. (2015) Donna Haraway: the digital cyborg assemblage and the new digital health technologies. In Collyer, F. (ed), The Palgrave Handbook of Social Theory in Health, Illness and Medicine. Houndmills: Palgrave Macmillan.

Peer-reviewed journal articles

Report

  • Lupton, D. and Pedersen, S. (2015) ‘What is Happening with Your Body and Your Baby’: Australian Women’s Use of Pregnancy and Parenting Apps. Available here.

Critical social research on self-tracking: a reading list

Self-tracking has recently become a new area of fascination for critical social researchers. A body of literature has now been established of research that has sought to investigate the social, cultural and political dimensions of self-tracking, nearly all of which has come out in the last few years. This literature complements an established literature in human-computer interaction research (HCI), first into lifelogging and then into self-tracking (or personal informatics/analytics, as HCI researchers often call it).

I am currently working on an article that is a comprehensive review of both literatures, in the attempt to outline what each can contribute to understanding self-tracking as an ethos and a practice, and its wider sociocultural implications. Here is a reading list of the work from critical social researchers that I am aware of. I will publish a similar list of interesting HCI research in a forthcoming post.

Albrechtslund, A, and P Lauritsen, (2013) Spaces of everyday surveillance: Unfolding an analytical concept of participation, Geoforum, 49: 310-16.

Allen, AL, (2008) Dredging up the past: Lifelogging, memory, and surveillance, The University of Chicago Law Review, 75 (1): 47-74.

Barta, K, and G Neff, (2015) Technologies for sharing: lessons from Quantified Self about the political economy of platforms, Information, Communication & Society, online first.

Bode, M, and DB Kristensen,  (2016) The digital doppelgänger within. In Assembling Consumption: Researching actors, networks and markets, edited by R. Canniford and D. Badje. London: Routledge, pp.

Bossewitch, J, and A Sinnreich, (2013) The end of forgetting: Strategic agency beyond the panopticon, New Media & Society, 15 (2): 224-42.

Copelton, D, (2010) Output that counts: pedometers, sociability and the contested terrain of older adult fitness walking, Sociology of Health & Illness, 32 (2): 304-18.

Crawford, K, J Lingel, and T Karppi, (2015) Our metrics, ourselves: A hundred years of self-tracking from the weight scale to the wrist wearable device, European Journal of Cultural Studies, 18 (4-5): 479-96.

Daly, A, (2015) The law and ethics of ‘self quantified’ health information: an Australian perspective, International Data Privacy Law, online first.

Dodge, M, and R Kitchin, (2007) ‘Outlines of a world coming into existence’: pervasive computing and the ethics of forgetting, Environment and Planning B: Planning & Design, 34 (3): 431-45.

Drew, DL, and JM Gore, (2014) Measuring up? The discursive construction of student subjectivities in the Global Children’s Challenge™, Sport, Education and Society, online first.

Fiore-Gartland, B, and G Neff, (2015) Communication, mediation, and the expectations of data: data valences across health and wellness communities, International Journal of Communication, 9: 1466-84.

Fox, NJ, (2015) Personal health technologies, micropolitics and resistance: a new materialist analysis, Health:, online first.

Gardner, P, and B Jenkins, (2015) Bodily intra-actions with biometric devices, Body & Society, online first.

Gerlitz, C, and C Lury, (2014) Social media and self-evaluating assemblages: on numbers, orderings and values, Distinktion: Scandinavian Journal of Social Theory, 15 (2): 174-88.

Gilmore, JN, (2015) Everywear: The quantified self and wearable fitness technologies, New Media & Society, online first.

Jethani, S, (2015) Mediating the body: Technology, politics and epistemologies of self, Communication, Politics & Culture, 47 (3): 34-43.

Klauser, FR, and A Albrechtslund, (2014) From self-tracking to smart urban infrastructures: towards an interdisciplinary research agenda on Big Data, Surveillance & Society, 12 (2): 273-86.

Lomborg, S, and K Frandsen, (2015) Self-tracking as communication, Information, Communication & Society: 1-13.

Lupton, D, (2012) M-health and health promotion: the digital cyborg and surveillance society, Social Theory & Health, 10 (3): 229-44.

Lupton, D, (2013a) The digitally engaged patient: self-monitoring and self-care in the digital health era, Social Theory & Health, 11 (3): 256-70.

Lupton, D, (2013b) Quantifying the body: monitoring and measuring health in the age of mHealth technologies, Critical Public Health, 23 (4): 393-403.

Lupton, D, (2013c) Understanding the human machine, IEEE Technology & Society Magazine, 32 (4): 25-30.

Lupton, D, (2014a) The commodification of patient opinion: the digital patient experience economy in the age of big data, Sociology of Health & Illness, 36 (6): 856-69.

Lupton, D, (2014b) Self-tracking cultures: towards a sociology of personal informatics. In Proceedings of the 26th Australian Computer-Human Interaction Conference (OzCHI ’14). Sydney: ACM Press.

Lupton, D. (2014c) Self-tracking modes: reflexive self-monitoring and data practices. Social Science Research Networkhttp://ssrn.com/abstract=2483549  (accessed 27 August 2014).

Lupton, D. (2014d) You are your data: self-tracking practices and concepts of data. Social Science Research Networkhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=2534211  (accessed 12 December 2015).

Lupton, D, (2015a) Data assemblages, sentient schools and digitised health and physical education (response to Gard), Sport, Education and Society, 20 (1): 122-32.

Lupton, D. (2015b) Lively data, social fitness and biovalue: the intersections of health self-tracking and social media. Social Science Research Networkhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=2666324  (accessed 13 November 2015).

Lupton, D. (2015c) Personal data practices in the age of lively data. Social Science Research Networkhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=2636709  (accessed 15 August 2015).

Lupton, D, (2015d) Quantified sex: a critical analysis of sexual and reproductive self-tracking using apps, Culture, Health & Sexuality, 17 (4): 440-53.

Lupton, D, (2016a) The diverse domains of quantified selves: self-tracking modes and dataveillance, Economy and Society, in press.

Lupton, D, (2016b) The Quantified Self: A Sociology of Self-Tracking Cultures. Cambridge: Polity Press.

Lynch, R, and S Cohn, (2015) In the loop: Practices of self-monitoring from accounts by trial participants, Health:, online first.

Millington, B, (2015) ‘Quantify the Invisible’: notes toward a future of posture, Critical Public Health, online first.

Moore, P, and A Robinson, (2015) The quantified self: What counts in the neoliberal workplace, New Media & Society, online first.

Nafus, D, (2013) The data economy of biosensors. In Sensor Technologies:  Healthcare, Wellness and Environmental Applications, edited by M. McGrath and C. N. Scanaill: Springer.

Nafus, D, (2014) Stuck data, dead data, and disloyal data: the stops and starts in making numbers into social practices, Distinktion: Scandinavian Journal of Social Theory, 15 (2): 208-22.

Nafus, D, and J Sherman, (2014) This one does not go up to 11: the Quantified Self movement as an alternative big data practice, International Journal of Communication, 8: 1785-94.

Neff, G, and D Nafus, (2016) Self-Tracking. Cambridge, MA: The MIT Press.

Niva, M, (2015) Online weight-loss services and a calculative practice of slimming, Health:, online first.

Pantzar, M, and M Ruckenstein, (2015) The heart of everyday analytics: emotional, material and practical extensions in self-tracking market, Consumption Markets & Culture, 18 (1): 92-109.

Reigeluth, TB, (2014) Why data is not enough: digital traces as control of self and self-control, Surveillance & Society, 12 (2): 243-54.

Rettberg, JW, (2014) Seeing Ourselves Through Technology: How We Use Selfies, Blogs and Wearable Devices to See and Shape Ourselves. Basingstoke: Palgrave Macmillan.

Ruckenstein, M, (2014) Visualized and interacted life: personal analytics and engagements with data doubles, Societies, 4 (1): 68-84.

Ruckenstein, M,  (2015) Uncovering everyday rhythms and patterns: food tracking and new forms of visibility and temporality in health care. In Techno-Anthropology in Health Informatics, edited by L. Botin, C. Nohr and P. Bertelsen. Amsterdam: IOS Press, pp. 28-40.

Ruckenstein, M, and M Pantzar, (2015a) Beyond the Quantified Self: thematic exploration of a dataistic paradigm, New Media & Society, online first.

Ruckenstein, M, and M Pantzar, (2015b) Datafied life: techno-anthropology as a site for exploration and experimentation, Techne, 19 (2): 191-210.

Sellen, AJ, and S Whittaker, (2010) Beyond total capture: a constructive critique of lifelogging, Communications of the ACM, 53 (5): 70-77.

Smith, WR, (2015) Communication, sportsmanship, and negotiating ethical conduct on the digital playing field, Communication & Sport, earlyview online.

Stragier, J, T Evens, and P Mechant, (2015) Broadcast yourself: an exploratory study of sharing physical activity on social networking sites, Media International Australia, 155 (1): 120-29.

Thomas, GM, and D Lupton, (2015) Threats and thrills: pregnancy apps, risk and consumption, Health, Risk & Society, online first.

Till, C, (2014) Exercise as labour: Quantified Self and the transformation of exercise into labour, Societies, 4 (3): 446-62.

Van Den Eede, Y,  (2015) Tracing the tracker: a postphenomenological inquiry into self-tracking technologies. In Postphenomenological Investigations: Essays on Human–Technology Relations, edited by R. Rosenberger and P.-P. Verbeek. Lanham, Maryland: Lexington Books, pp. 143-58.

Whitson, J, (2013) Gaming the quantified self, Surveillance & Society, 11 (1/2): 163-76.

Wilkinson, J, C Roberts, and M Mort, (2015) Ovulation monitoring and reproductive heterosex: living the conceptive imperative?, Culture, Health & Sexuality, 17 (4): 454-69.

Williamson, B, (2015) Algorithmic skin: health-tracking technologies, personal analytics and the biopedagogies of digitized health and physical education, Sport, Education and Society, 20 (1): 133-51.

Yang, Y, (2014) Saving the Quantified Self: How we come to know ourselves now, Boom: A Journal of California, 4 (4): 80-87.

 

 

 

 

Towards a new mode of self-tracking

In a conference paper and my forthcoming book The Quantified Self: A Sociology of Self-Tracking Cultures, I identify five modes of self-tracking. What I call ‘private self-tracking’ is undertaken for voluntary and personal reasons that are self-initiated. ‘Pushed self-tracking’ involves encouragement for people to monitor themselves from other agencies, while the mode of ‘communal self-tracking’ relies on people sharing their personal information with others. ‘Imposed self-tracking’ involves moving from encouragement to requiring people to collect or engage with data about themselves, so that they may have little choice in doing so. The ‘exploited self-tracking’ mode represents the ways in which personal data may be used by other actors and agencies for their own purposes, either overtly or covertly.

Since writing the initial conference paper, developing these ideas in my book and also for a journal article based on the paper, I have added some thoughts about the possibilities for forms of self-tracking that go beyond these modes. As I argue, self-tracking conforms to a conservative political agenda that represents citizens as automated/autonomous subjects, ideally engaging in self-responsibilised practices of monitoring and life optimisation and emitting valuable ‘data exhausts’ for repurposing by other actors and agencies.

As yet, there has been little discussion of the ways in which self-tracking may be used for resistant or strategic political interventions – as means to challenge accepted norms and assumptions about selves and bodies rather than conforming to these norms and assumptions. Few commentators have drawn attention to how self-tracking highlights certain forms of information about specific kinds of individuals or social groups while it neglects or ignores others, and how idealised citizen subjects are configured via dominant self-tracking cultures while those who fail to meet these ideals are stigmatised or disciplined.

Nascent moves towards a more political use of self-tracking are evident in some citizen sensing initiatives, when they are used to expose or challenge assumptions about geographical areas, the social determinants of ill-health, the environment and living conditions in the effort to draw attention towards social inequalities, government neglect or environmental mismanagement.

There is ample further scope for alternative approaches to self-tracking as a form of knowledge production that seek to identify, record and highlight details of socioeconomic disadvantage or social stigma rather than simply perpetuating them, or to generate knowledge of others rather than being directed at serving the solipsism of self-knowledge. Resistant self-tracking efforts may serve to make visible forms of power relations, injustice and inequalities that are currently hidden from view. It is here that a new mode of self-tracking may develop. The possibilities for a new form of data politics that takes up these more critical and challenging practices are intriguing.

Digitising female fertility and reproduction

Over the past few months, I have been working on writing about the findings of several research projects addressing the topic of digital technologies directed at female fertility and reproduction. These projects involve:

1) a critical content analysis of fertility and reproduction-related software and devices (especially apps);

2) an online survey of 410 Australian women’s use of pregnancy and parenting apps; and

3) focus groups and interviews with Australian and British women about their use of these technologies (these are still in progress).

Several outcomes have now been published drawing on these findings. They include a report (with Sarah Pedersen from Robert Gordon University, Aberdeen) outlining the findings of the online survey (this can be accessed here), an article on the gamification and ludification of pregnancy in apps (with Gareth Thomas from Cardiff University, available here) and a book chapter on the concept of the reproductive citizen and the range of digital technologies that are directed at helping women to monitor and regulate their fertility and reproduction (available here). Edit: two other articles have now been published: one based on the survey findings (here), and another on the pregnancy app study (here).

Some of the key findings are:

  • The survey showed that pregnancy and parenting apps were very popular among the survey respondents – three-quarters of the respondents (who were either pregnant or who had a baby in the past three years at the time of the survey) said that they had used at least one pregnancy app, while almost half had used at least one parenting app.
  • Googling information about pregnancy is very common among pregnant women, for whom too much information about pregnancy appears never to be enough (this finding emerged in the focus groups). They tend to invest their trust in the first few search findings that come up on their search engine, reasoning that because this is evidence of popularity, then these websites must be credible.
  • Despite the popularity of pregnancy and parenting apps, few women are contemplating the validity of the information presented in them, or demonstrated concern about the data security and privacy of the personal information that the apps may collect (this was evident in both the survey and the focus groups).
  • This genre of software is intensifying an already fervid atmosphere of self-surveillance, attempts at management and control and self-responsibility in which female fertility and reproduction are experienced and performed.
  • Stereotypical concepts of idealised female fertile and pregnant bodies are reproduced in apps and other software. They use highly aestheticised images and the promise of rational calculation and monitoring to seek to contain and control women’s fertility and reproduction.
  • Women in their fertile years – and particularly those contemplating pregnancy or already pregnant – are part of a highly commodified demographic. The information that they generate from their online practices possess a new form of value, biovalue, as part of the bioeconomy of personal health and medical data.

Self-tracking, social fitness and biovalue

I have just completed a chapter for the forthcoming volume The Sage Handbook of Social Media. The chapter addresses the intersections of self-tracking for health and medical purposes with social media platforms and rationales. As I argue in the chapter, the expanded array of digitised devices that are available for self-tracking and the capacity of many of these technologies to interact with social media platforms have encouraged self-trackers to share the details that they collect about themselves with others. I begin with a description of self-tracking and the sociomaterial theoretical foundations on which the chapter rests. This is followed with an overview of the technologies that are available for health and medical self-tracking and for self-trackers to share their data. The discussion section of the chapter presents an analysis of the new forms of value that personal health and medical data have attracted in the digital data economy, and the moral and political repercussions of encouraging people to participate as socially fit citizens. The chapter ends with outlining key questions for further research.

The full pre-print of the chapter is available here.

Digitised children’s bodies

This is an excerpt from the pre-print version of a chapter I have written on the topic of ‘digital bodies’. The full pre-print can be accessed here.

The sociomaterialist perspective has been taken up by several scholars writing about children’s bodies, particularly within cultural geography, but also by some sociologists and anthropologists (Prout, 1996; Horton and Kraftl, 2006a, 2006b; Lee, 2008; Woodyer, 2008). Researchers using a sociomaterialist approach have conducted studies on, for example, children’s use of asthma medication (Prout, 1996), the surveillant technologies that have developed around controlling children’s body weight in schools (Rich et al., 2011), children’s sleep and the objects with which they interact (Lee, 2008), the interrelationship of objects with pedagogy and classroom management of students’ bodies (Mulcahy, 2012) and sociomaterial practices in classrooms that lead to the inclusion or exclusion of children with disabilities (Söderström, 2014). Outside sociomaterialist studies, young children’s interactions with digital technologies have attracted extensive attention from social researchers, particularly in relation to topics such as the potential for cyber-bullying, online paedophilia and for children to become unfit and overweight due to spending too much time in front of screens (Holloway et al., 2013). However few researchers thus far have directed their attention to the types of digital technologies that visually represent children’s bodies or render their body functions, activities and behaviours into digital data; or, in other words, how children’s bodies become digital data assemblages.

From the embryonic stage of development onwards, children’s bodies are now routinely monitored and portrayed using digital technologies. A plethora of websites provide images of every stage of embryonic and foetal development, from fertilisation to birth, using a combination of digital images taken from embryo and foetus specimens and digital imaging software  (Lupton, 2013). 3/4D ultrasounds have become commodified, used for ‘social’ or ‘bonding’ purposes. Many companies offering 3/D ultrasounds now come to people’s homes, allowing expectant parents to invite family and friends and turn a viewing of the foetus into a party event. This sometimes involves a ‘gender reveal’ moment, in which the sonographer demonstrates to all participants, including the parents, the sex of the foetus . Some companies offer the service of using 3D ultrasound scan files to create life-sized printed foetus replica models for parents.

The posting to social media sites such as Facebook, Twitter, Instagram and YouTube of the foetus ultrasound image has become a rite of passage for many new parents and often a way of announcing the pregnancy. Using widgets such as ‘Baby Gaga’, expectant parents can upload regular status updates to their social media feeds automatically that provide news on the foetus’s development. While a woman is pregnant, she can use a range of digital devices to monitor her foetus. Hundreds of pregnancy apps are currently on the market, including not only those that provide information but others that invite users to upload personal information about their bodies and the development of their foetus. Some apps offer a personalised foetal development overview or provide the opportunity for the woman to record the size of her pregnant abdomen week by week, eventually creating a time-lapse video. Other apps involve women tracking foetal movements or heart beat. Bella Beat, for example, is a smartphone attachment and app that allows the pregnant women to hear and record the foetal heart beat whenever she likes and to upload the audio file to her social media accounts.

YouTube has become a predominant medium for the representation of the unborn entity in the form of ultrasound images and of the moment of birth. Almost 100,000 videos showing live childbirth, including both vaginal and Caesarean births, are available for viewing on that site, allowing the entry into the world of these infants to be viewed by thousands and, in the case of some popular videos, even millions of viewers. Some women even choose to live-stream the birth so that audiences can watch the delivery in real time. Following the birth, there are similar opportunities for proud parents to share images of their infant online on social media platforms. In addition to these are the growing number of devices on the market for parents to monitor the health, development and wellbeing of their infants and young children. Apps are available to monitor such aspects as infants’ feeding and sleeping patterns, their weight and height and their development and achievements towards milestones. Sensor-embedded baby clothing, wrist or ankle bands and toys can be purchased that monitor infants’ heart rate, body temperature and breathing, producing data that are transmitted to the parents’ devices. Smartphones can be turned into baby monitors with the use of apps that record the sound levels of the infant.

As children grow, their geolocation, educational progress and physical fitness can be tracked by their parents using apps, other software and wearable devices. As children themselves begin to use digital technologies for their own purposes, they start to configure their own digital assemblages that represent and track their bodies. With the advent of touchscreen mobile devices such as smartphones and tablet computers, even very young children are now able to use social media sites and the thousands of apps that have been designed especially for their use (Holloway et al., 2013). Some such technologies encourage young children to learn about the anatomy of human bodies or about nutrition, exercise and physical fitness, calculate their body mass index, collect information about their bodies or represent their bodies in certain ways (such as manipulating photographic images of themselves). These technologies typically employ gamification strategies to provide interest and motivation for use. Some involve combining competition or games with self-tracking using wearable devices. One example is the Leapfrog Leapband, a digital wristband connected to an app which encourages children to be physically active in return for providing them with the opportunity to care for virtual pets. Another is the Sqord interactive online platform with associated digital wristband and app. Children who sign up can make an avatar of themselves and use the wristband to track their physical activity. Users compete with other users by gaining points for moving their bodies as often and as fast as possible.

In the formal educational system there are still more opportunities for children’s bodies to be monitored measured and evaluated and rendered into digitised assemblages. Programmable ‘smart schools’ are becoming viewed as part of the ‘smart city’, an urban environment in which sensors that can watch and collect digital data on citizens are ubiquitous (Williamson, 2014). The monitoring of children’s educational progress and outcomes using software is now routinely undertaken in many schools, as are their movements around the school. In countries such as the USA and the UK, the majority of schools have CCTV cameras that track students, and many use biometric tracking technologies such as RFID chips in badges or school uniforms and fingerprints to identify children and monitor their movements and their purchases at school canteens (Taylor, 2013; Selwyn, 2014). A growing number of schools are beginning to use wearable devices, apps and other software for health and physical education lessons, such as coaching apps that record children’s sporting performances and digital heart rate monitors that track their physical exertions (Lupton, 2015).

We can see in the use of digital technologies to monitor and represent the bodies of children a range of forms of embodiment. Digitised data assemblages of children’s bodies are generated from before birth via a combination of devices that seek to achieve medical- or health-related or social and affective objectives. These assemblages may move between different domains: when, for example, a digitised ultrasound image that was generated for medical purposes becomes repurposed by expectant parents as a social media artefact, a way of announcing the pregnancy, establishing their foetus as new person and establishing its social relationships. Parents’ digital devices, and later those of educational institutions and those of children themselves when they begin to use digital devices, potentially become personalised repositories for a vast amount of unique digital assemblages on the individual child, from images of them to descriptions of their growth, development, mental and physical health and wellbeing, movements in space, achievements and learning outcomes. These data assemblages, containing as they do granular details about children, offer unprecedented potential to configure knowledges about individual children and also large groups of children (as represented in aggregated big data sets).

References

Holloway D, Green L and Livingstone S. (2013) Zero to Eight: Young Children and Their Internet Use. London: LSE London, EU Kids Online.

Horton J and Kraftl P. (2006a) Not just growing up, but going on: Materials, spacings, bodies, situations. Children’s Geographies 4(3): 259-276.

Horton J and Kraftl P. (2006b) What else? some more ways of thinking and doing ‘Children’s Geographies’. Children’s Geographies 4(1): 69-95.

Lee N. (2008) Awake, asleep, adult, child: An a-humanist account of persons. Body & Society 14(4): 57-74.

Lupton D. (2013) The Social Worlds of the Unborn, Houndmills: Palgrave Macmillan.

Lupton D. (2015) Data assemblages, sentient schools and digitised health and physical education (response to Gard). Sport, Education and Society 20(1): 122-132.

Mulcahy D. (2012) Affective assemblages: body matters in the pedagogic practices of contemporary school classrooms. Pedagogy, culture and society 20(1): 9-27.

Prout A. (1996) Actor-network theory, technology and medical sociology: an illustrative analysis of the metered dose inhaler. Sociology of Health and Illness 18(2): 198-219.

Rich E, Evans J and De Pian L. (2011) Children’s bodies, surveillance and the obesity crisis. In: Rich E, Monaghan LF and Aphramor L (eds) Debating Obesity: Critical Perspectives. Houndsmills: Palgrave Macmillan, 139-163.

Selwyn N. (2014) Data entry: towards the critical study of digital data and education. Learning, Media and Technology: 1-19.

Söderström S. (2014) Socio-material practices in classrooms that lead to the social participation or social isolation of disabled pupils. Scandinavian Journal of Disability Research online first.

Taylor E. (2013) Surveillance Schools: Security, Discipline and Control in Contemporary Education, Houndmills: Palgrave Macmillan.

Williamson B. (2014) Smart schools in sentient cities. dmlcentral.

Woodyer T. (2008) The body as research tool: embodied practice and children’s geographies. Children’s Geographies 6(4): 349-362.

Managing and materialising data as part of self-tracking

Like many other forms of digital data, self-tracking data have a vitality and social life of their own, circulating across and between a multitude of sites. In a context in which digital data are culturally represented as liquid entities that require management and containment, part of the project of managing the contemporary body is that of containment of the data that one’s body produces. As discursive representations of self-tracking and the quantified self frequently contend, personal data are profligate: it is only right that one should seek first, to collect these data, and second, to manage and discipline the data by aggregating them, representing them visually, and making sense of them.

Shifting forms of selfhood are configured via these digital data assemblages, depending on the context in and purpose for which they are assembled. As the digital data produced by self-tracking are constantly generated and the combinations of data sets that may be brought together on individuals are numerous, personal data assemblages are never stable or contained. They represent a ‘snap-shot’ of a particular moment in time and a particular rationale of data practice. The data assemblages are always mutable, dynamic, responsive to new inputs and interpretations. They thus represent a type of selfhood that is distributed between different and constantly changing data sets. Self-tracking assemblages are constantly created and recreated when information about individuals is derived via digital technologies and then reassembled for various purposes.

Bodies and selves are always multiple, in whatever context they find themselves. However for self-trackers, this multiplicity is foregrounded in ways that may not have occurred in previous eras. If they are reviewing their personal data regularly, they cannot fail to be confronted with the shifting data assemblages that serve to represent their bodies and their selves. Part of the data practices in which they are invited to engage as part of self-tracking culture, therefore, is the negotiation and sense-making around the hybridity and vitality of their data assemblages.

To gain meaning from these data sets, self-trackers or third parties who seek to use their data must engage in sense-making that can interpret these data and gain some purchase on their mutating forms. An important element of self-tracking practices for many people is the visualisation or presentation of their personal data. The notion that data can be beautiful and aesthetically pleasing when presented in appropriate formats pervades data science in general: Gregg (2015) refers to this phenomenon as the ‘data spectacle’. The generation of digital data visualisations can be, variously, acts of work, creative expression and the presentation or performance of selfhood, with the latter an element in particular of self-tracking practices.

In the ‘show-and-tell’ ethos of the Quantified Self movement, finding compelling visual modes to demonstrate the patterns in one’s data is a central feature. The Quantified Self website is full of demonstrations by members of their data, including videos of their ‘show-and-tell’ presentations and still images of their visualisations. Collecting and aggregating personal data, therefore, are part of a range of practices involving self-knowledge and self-expression. By showing one’s data to others in a visually interesting and explanatory graphic, a self-tracker is achieving both self-knowledge and self-expression. Self-tracking becomes performative, both for the insights that a self-tracker may achieve about her or his life but also in terms of the aesthetics of the data that she or he may be able to curate.

The aesthetic elements of data visualisations involve affective responses that may include both pleasure and anxiety (McCosker and Wilken 2014). Indeed McCosker and Wilken (2014) refer to the tendency in data visualisation circles towards the fetishising and sublimity of ‘beautiful data’ as part of exerting mastery over the seemingly unlimited and thus overwhelming amounts of big digital datasets. Extending this logic, the physical materialising of digital data in the form of a 2D or 3D data materialisation may offer a solution to the anxieties of big data. When it is one’s personal data drawn from one’s own flesh that is being manifested in a material digital data object, this may provoke a sense of mastery over what may be experienced as a continually data-emitting subjectivity. The liquidity, flows and force of personal digital data become frozen in time and space, offering an opportunity to make sense of one’s data.

Edit (12 December 2015): More on this topic can be found in my book The Quantified Self: A Sociology of Self-Tracking.

References

Gregg, M. (2015) Inside the data spectacle. Television & New Media, 16 (1), 37-51.

McCosker, A. and Wilken, R. (2014) Rethinking ‘big data’ as visual knowledge: the sublime and the diagrammatic in data visualisation. Visual Studies, 29 (2), 155-164.

Changing representations of self-tracking

I recently completed a chapter for a book on lifelogging that discussed the concepts and uses of data as they are expressed in representations of self-tracking (see here for the full paper, available open access). In part of the chapter I looked at the ways in which people writing about the quantified self and other interpretations of self-tracking represent data and data practices, including in articles published in Wired magazine and other media outlets and blogs.

From the beginning of discussions of the quantified self, the representation of data in quantified self-tracking discourses (as least as it was expressed by its progenitors) included several factors. These include the following: quantified data are powerful entities; it is important not only to collect quantified data on oneself, but to analyse these data for the patterns and insights they reveal; data (and particularly quantified or quantifiable data) are an avenue to self-knowledge; the emergence of new digital and mobile devices for gathering information about oneself have facilitated self-tracking and the generation of quantified personal data; quantifiable data are more neutral, reliable, intellectual and objective than qualitative data, which are intuitive, emotional and subjective; self-tracked data can provide greater insights than the information that a person receives from their senses, revealing previously hidden patterns or correlations; self-tracked data can be motivational phenomena, inspiring action, by entering into a feedback loop; everything can be rendered as data; and data about individuals are emblematic of their true selves.

In more recent times, however, it is evident that a further set of concepts about self-tracked data have emerged since the original euphoria of the early accounts of quantified self-tracking. They include: the meaning of self-tracked data can be difficult to interpret; personal data can be disempowering as well as empowering; the conditions in which data are gathered can influence their validity; the contexts in which data are generated are vital to understanding their meaning; individuals’ personal data are not necessarily secure or private; quantified personal data can be reductive; and personal data can be used to discriminate against individuals.

We as yet know very little about how people are conceptualising and engaging with digital data about themselves. Given the recent scandals about how people’s personal data may be hacked or used or manipulated without their knowledge (the Snowden revelations about security agencies’ use of metadata, the Facebook emotional manipulation experiment, the celebrity nude photo and Sony Pictures hackings, for example), as well as growing coverage of the potentially negative implications of self-tracking as described above, these are pressing issues.

Edit (12 December 2015): More on this topic can be found in my book The Quantified Self: A Sociology of Self-Tracking Cultures.

 

The cultural specificity of digital health technologies

Digital health technologies configure a certain type of practising medicine and public health, a certain type of patient or lay person and a specific perspective on the human body. The techno-utopian approach to using digital health technologies tends to assume that these tacit norms and assumptions are shared and accepted by all the actors involved, and that they are acting on a universal human body. Yet a cursory examination of surveys of digital health technology use demonstrates that social structural factors such as age, gender, education level, occupation and race/ethnicity, as well as people’s state of health and their geographical location play a major role in influencing how such technologies are taken up among lay people or the extent to which they are able to access the technologies.

An American study of the use of some digital health technologies using representative data collected by the National Cancer Institute in 2012, for example, found no evidence of differences by race or ethnicity, but significant differences for gender, age and socioeconomic status (Kontos et al. 2014). Female respondents were more likely to use online technologies for health-related information, as were younger people (under less than 65) and those of higher socioeconomic status. People of low socioeconomic status were less likely to go online to look for a healthcare provider, use email or the internet to connect with a doctor, track their personal health information online, using a website to track to help track diet, weight or physical activity or download health information to a mobile device. However they were more likely to use social media sites to access or share health information. Women were more likely than men to engage in all of these activities.

While there is little academic research on how different social groups use apps, market research reports have generated some insights. One report showed that women install 40 per cent more apps than men and buy 17 per cent more paid apps. Men use health and fitness apps slightly more (10 per cent) than women (Koetsier 2013). A Nielsen market report on the use of wearable devices found that while men and women used fitness activity bands in equal numbers, women were more likely to use diet and calorie counter apps (Nielsen 2014).

As these findings suggest, gender is one important characteristic that structures the use of digital health technologies. The digital technology culture is generally male-dominated: most technology designers, developers and entrepreneurs are male. As a result, a certain blindness to the needs of women can be evident. For example, when the Apple Health app was announced in 2014, destined to be included as part of a suite of apps on the Apple Watch, it did not include a function for the tracking of menstrual cycles (Eveleth 2014). Gender stereotypes are routinely reproduced in devices such as health and medical apps. As I noted in my study of sexuality and reproduction self-tracking apps, the sexuality apps tend to focus on documenting and celebrating male sexual performance, with little acknowledgement of women’s sexuality, while reproduction apps emphasise women’s over men’s fertility.

App designers and those who develop many other digital technologies for medical and health-related purposes often fail to recognise the social and cultural differences that may influence how people interact with them. Just as cultural beliefs about health and illness vary from culture to culture, so too do responses to the cultural artefacts that are digital health technologies. Aboriginal people living in a remote region of Australia, for example, have very different notions of embodiment, health and disease from those that tend to feature in the health literacy apps that have been developed for mainstream white Australian culture (Christie and Verran 2014). It is therefore not surprising that a review of the efficacy of a number of social media and apps developed for health promotion interventions targeted at Aboriginal Australians found no evidence of their effectiveness or benefit to this population (Brusse et al. 2014).

Few other analyses have sought to highlight the cultural differences in which people respond to and use digital health technologies. This kind of research is surely imperative to challenge existing assumptions about ‘the user’ of these technologies and provide greater insights into their benefits and limitations.