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«Tactics of Diabetes Control Turkish immigrant experiences with chronic illness in Berlin, Germany. Cornelia Guell PhD by Research The University of ...»

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As in the previous chapter, this is not so much about health or the ill body but about those people and places that form around diabetes care. By that I mean, this chapter is not about politics on the diabetic body (e.g. as in Foucault's biopolitics) but about politics because of diabetic bodies. It thus includes a wide range of people, not only those living with diabetes or health professionals in diabetes care.

8.1 Berlin’s field of informal diabetes care My ethnographic investigation of Berlin’s Turkish diabetes biosociality proved a diverse and eventful endeavour. I not only encountered doctors and their patients, clinical settings and private homes but active interest groups like the self-help group and the medics’ society and the enigmatic personalities that led such groups, shaped activities, interactions and avenues of involvement. People would describe this interaction as a network of informal diabetes care. Trying to disentangle these relations and structures analytically, I deliberately use the organic metaphor field.

Neither the locally used “network”, nor more recent technologically framed concepts of “assemblages” or “biocrossings” can account for the complex and fluent involvements and interactions that I encountered but imply deliberate structure, organisation or construction. After deciding to describe this activity and sociality around diabetes care as a field, I explore the kind of people who occupy this field, the varied roles that belong to this field and the varied settings and events as such roles are taken up.

Diabetes as a network During my fieldwork participants frequently evoked the imagery of network (in German Netzwerk). They referred to themselves as networkers in healthcare and regarded diabetes as an ultimate “network illness”. They explained that diabetes affects a whole network of organs that are connected and compromised in their function by the sweet blood of the diabetic body. Glucose-rich blood clogs arteries and strains the kidneys; it damages the nerves of eyes, hands and feet. Diabetes care, therefore, requires the attention of a network of health professionals: the family doctor, the diabetologist, the nutritionists, the podiatrist, the ophthalmologist (eye specialist), the cardiologists, the nephrologist, the social worker and so on and so forth. These health professionals should ideally work together and form a therapeutic network in the interests of the patient. While this “network ideal” was shared by many involved, tensions between participants of this evoked network resulted in a general frustration and cynicism that it was, in fact, a dysfunctional network which was more guided by financial competition and personal feuds than genuine professional concern for the patient.

My own conceptualisation of above relations, collaboration and dissonance was, halfway through my fieldwork, also readily framed as a local, informal network of diabetes care. This invites reference to Riles’ (2001: The network inside out) consideration that in some of our contemporary research projects our analytical tools have already been appropriated by the research participants. “Network” is a concept widely used in healthcare, public health and health NGO circles37. Yet social network analysis is also an established analytical and methodological approach in (mainly quantitative) social sciences. Scott (2000: 2) describes social network analysis as the analytical tool for relational data, i.e. the data of contacts, ties and connections, group attachments and meetings which relate one agent to another – as opposed to attribute data of attitudes, opinions and behaviours of agents (which requires variable analysis, i.e. the analysis of variables such as income, occupation, education etc.). I attempted a social network analysis during my fieldwork, when I realised that the diabetes patients I met at the self-help group shared the demographics of poor, uneducated, first generation migrants, yet showed confident diabetes knowledge and control. The difference was, of course, their belonging to the group, and their social relations that made access to knowledge and support possible.

Social network analysis was developed in order to investigate social structure rather than function, and as sociologists saw networks in particular as a (new) way of capturing social structure. Some (e.g. Mitchell in Scott 2000: 32) insist on a further distinction of networks of interpersonal relations and structures of institutional relations, thus distancing themselves from general structuralists. The earliest, most formative social network analysis are Lee’s (1969) study on how information on (illegal) abortionists is acquired by women, and Granovetter’s Getting a Job (1974), On networks of care, e.g. see Horden and Smith (1998); on the impact of social networks on health, e.g. on stress and mental health, see Haines and Hurlbert (1992); on sexual networks and HIV transmission, Parker (2006); on religious social networks, which try to fill gaps of governmental social welfare, see Clark (2004); Cooke and Lawrence (2005).

in which he famously discovered that it is in fact weak, not strong, social links through which vital and new information is acquired. Both studies were interested in knowledge networks, that means how knowledge is transported through social networks and how these networks are maintained.

Later developments of social network analysis moved increasingly away from a pure methodological approach and saw “network analysis as basis of a relational sociology”, replacing “approaches that have stressed culture and meaning” (Scott 2000: 37). This, however, assumes that it is the structure that is interesting about networks not which meaning actors attribute to these structures. Social network analysis analyses connections and their density and direction. This fails to account for what makes such connections meaningful, for example to explore the basis of such ties as a joint endeavour to provide informal healthcare and to share, for example knowledge, and what kind of knowledge is shared, negotiated, or withheld.





Moreover, social network analysis does not provide a framework to map hierarchies and dominations, sympathies and antipathies, solidarity and tension.

Nonetheless, some anthropologists have valued the analytical qualities of social network theory. The urban anthropologist Boissevain (1979: 392) saw it as a “tool which enables […] to deal with the relation between face-to-face interaction and institutions in an extremely complex social field. […] Network analysis asks questions about who is linked to whom, the content of the linkages, the pattern they form, the relation between the pattern and behaviour, and the relation between the pattern and other societal factors.” Boissevain, however, queried the overemphasis on technique and data, the reliance on mathematics and methodology rather than “human life” and wondered if a purely quantitative focus on network structures produces trivial (descriptive) results rather than helping to understand these structures. Wellman (1983: 165) agrees with seeing a value in social network analysis as previous studies tended to lump people, for example white, female, Protestant, American, voting Democrat, as one group neglecting social structures and the relations among individuals. As much as he can see merits in the development of mathematical tools he also commends new approaches of using fieldwork and archival methods to study network structures (Roberts 1973; Bodemann 1980). He suggests: “The essence of the network approach remains not in the method used but in posing questions and searching for answers in terms of structured connectivity.” (Wellman 1983: 171/172) My own attempt of an anthropological social network analysis helped to place emphasis on a network of diabetes care, the local interactions and transactions that alluded to more than commonalities of Turkishness or diabetes, of being a patient or doctor, and identified sites of relevance, for example town and wedding halls, that were not anticipated. Yet I soon realised that an ethnographic exploration struggles to come up with the neat structures, connections, nodes and focal points that a social network analysis requires (just as my research participants struggled to map the neat network ideal on their lived experience of “networking”). Law and Mol (2002) argue that such structural approaches aim and fail to simplify and order “complexities”. Accounting for complexities, they argue that networks cannot be neatly traced, “they add up and do not add up” at the same time, are both “functional” and “dysfunctional”, and there are multiplicities of networks. My research participants formed indeed connections in what they perceived as diabetes networks but the network idea could not – neither as a method, nor a metaphor – capture that interactions were fairly unstructured and messy, some ties broken or disrupted by conflict. Most importantly, it could not portray that individuals could occupy various positions and roles within these interactions, be patient, client, activist and expert at the same and different sites and time.

Assemblages, biocrossings and fields The notion of networks implies ordered structure, a certain completeness that neither my ethnographic methods could fulfil nor one that seems particular fitting to describe what is going on in multiple layers, positions and sites. Indeed it is commonly suggested to refrain from using the same terminology as research participants, in order to step back analytically. Commonly used in recent years is the idea of “assemblages” as the concept that tries to capture loose and partial connections (Strathern 2004a), changing scapes, formations and procedures, involving bodies, technologies, ethics and political economies (see e.g. contributions in the edited volume of Ong and Collier 2005). Gibbon and Novas (2008: 1) thus describe Rabinow's concept of biosociality as “biologies and socialities that are being assembled by a range of practitioners and social actors across a variety of interconnected sites such as laboratories, biotechnology companies, patients' organisations, medical clinics, biomedical charities and state institutions”. While this concept of assemblages captures well the complexities of involvements across domains while, unlike the notion of network, also suggesting certain unpredictabilities (Bharadwaj 2008), I fear the rather mechanic assemblage metaphor nonetheless alludes too much to a technical construction.

Bharadwaj (2008) proposes the notion of biocrossings in his exploration of IVF and embryonic stem cell technology. His scope ranges from cells, tissues and bodies to the state, science and capital, and understands biocrossings as “transfers between biology and machine and across geo-political, commercial, ethical and moral borders” (ibid. 102). Moreover, with his idea of biocrossings he expands “bio” from human biology to “biologically based biography, be it individual (e.g. an illness narrative or cultural/‘ethno’ conception of human body) or institutional (bioscience/medicine/technology etc.)” (ibid. 102). Such “bios” are altered through “multiple crossings across various borders and thresholds [...] imploding boundaries between nature, culture, biology and society” (ibid. 103). Again, however, such conceptualisation implies technologies, new futures that are bio-transformed and transforming the bio.

As I argued in the previous chapter, in the case of diabetes-related biosociality, despite all postmodern complexities of fluent positions across domains of social, political and moral economies, I suggest that something much more mundane is going on, nothing radically “cyborg”, no changed futures of biologies or lives (cf. Haraway 1991). This is not to say that technologies do not take up spaces and roles in such interactions; clinical number and glucose meters, for example, influence how both individuals make sense of their experience as well as how interactions and transactions between groups and individuals are shaped.

Nonetheless, there are no new media and communications involved.

Searching for an appropriate concept to understand such connected sociality around diabetes care in Berlin, I propose the, perhaps old-fashioned, term “field”.

Field, in my opinion, does not imply a network structure of specific focal points, nodes and linear connections, nor does it allude to the technical or “cyborg” constructions that assemblages connote. Field is a less “high-tech” metaphor, more organic. It allows for, but does not delineate, connections, assumes participants but without static positions. Note that I am duly omitting the idea of a “level playing field” in my conceptualisation, as “my field” is riddled with trenches and fences, with hierarchical structures, power inequalities, discordances and encumbrances.

Positions and roles What does this field of Berlin’s Turkish diabetes care, then, look like, and why does it require an organic metaphor for description? Involved was a variety of individuals, groups, places and domains. My particular focus was on the self-help group and their awkwardly opposing organisation, the medics’ society. Certain colourful personalities such as Yılmaz and doctors like his friend Dr. S seemed to dominate such groups and their representation, yet equally influential seemed quieter individuals such as the patient consultant Hilal, the drug rep Sedat, or self-help group members such as Rana, Sevim and Feyza. I paid less attention to – in my opinion – more marginally influential activities of certain NGOs and working groups, and the business of private nursing care. Yet all these individuals, groups and organisations shared their involvement in local diabetes provision; that is why I tried to organise them in some sort of informal network of diabetes care. The notion of network became a problematic one as any attempt to ascribe roles and settings – and events – to certain people and groups in some sort of graphic mapping failed. A mapping failed because people held multiple roles and positions. Unlike other biosocial literature, I met not only the patient, the scientist, the drug representative. While such literature imagines the patient-cum-activist, I encountered the patient-cum-activistcum-businessman-cum-manager. I began to list typologies of those involved in

healthcare:



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