Tuesday, July 15, 2014

Data are never just data

When we interact with individuals, households, communities in our fieldwork, we do so as social scientists.

The traditional framework of the social sciences have taught us to name the people we converse with as participants or respondents in our social scientific projects.

The participants are sources of data.

Data that we can then plug into our excel files or NVivo coding sheets for the purposes of sense making. In the confines of our labs , we then run our analyses, often through software packages such as SPSS and NVivo, seeking to glean patterns of thought, emotions, and behaviors, and correlating these patterns with other patterns. We observe the correlation between social class and health information seeking, the patterns of experiences among foreign domestic workers, the remittance patterns of male construction workers that have migrated from China etc.

We then write up these results in our discipline specific journals in disciplined language, giving a seemingly objective and distanced reading of the patterns that are gleaned from the data. We formulate theories on the basis of these observations, participating in academic production that incentivizes our labor through bonuses, salary raises, tenure and promotion etc.

What I find troubling in this traditional treatment of the people we speak with as data (and as just that, data) is first and foremost the complete erasure of their person-hood. We forget to acknowledge the humanity of the other that participates with us in conversation.

As sources of data, this other becomes a narrative or a number. Irrespective of whether one does quantitative or qualitative research, there is little commitment on behalf of the researcher to building a relationship with "the participant." In fact, good research is often defined as research that models for itself this distance from the people who have given part of themselves to make up the data we work with.

How often have I witnessed academics who just drop in to a community and then are gone. There is very little commitment to really getting to know the people behind the faces and the articulations, the households aggregated as data points, or the communities captured in indicators of social capital, social cohesion, and trust. There is also very little commitment to rigor. You see, much of the body of academic work is based on thin data that are collected through one time interactions, and social scientists are not held accountable to the context. You see, rigor is often not measured in relationship to the context. The narratives are not held accountable to the people who are the sources of the narratives. Instead, academic peer reviewers, trained in the same set of normative principles, become the judges of rigor, often based on narrowly prescriptive steps, procedures, and metrics.

Second, I am troubled with the exploitative nature of the relationship that defines human beings solely as data. This is especially the case when one works with workers who have been exploited, community members who have been disenfranchised, or sub-populations that have been denied access. In such instances, the selling of the academic career is often tied to the ability to market a narrative that exoticizes the other as the subject of academic work. The radical space of the marginalized narrative becomes the radical voice of the scholar while the participant continues to live amid the marginalizing processes that constitute her  or his lived experiences. Scholars are not held accountable to standards of making a difference in the contexts where they conduct the work. Quite to the contrary, the bourgeoisie expectations of academic work criticize scholars who become involved in the communities where they work.

Finally, I am struck by the very little impact of academic work,  especially social scientific work when it comes to questions of social impact in communities experiencing marginalization. Once again, this I believe is the very product of the organizing of the social sciences in incentive structures that privilege distance, lack of commitment, and elitism. Academics can recycle their academic theories in their privileged and little read academic journals, count the impact factor of their work by looking at how many other academics cited them, and enjoy their roles as experts. And all this is rewarded within universities [I myself have been rewarded through the university structure by making arguments to such metrics].

But whether their work truly made a difference in the lives of their data is something social scientists are not trained to ask. So it is fine to gather data on remittance patterns of male migrant workers and yet not spend a day thinking about the problems and issues faced by the male migrant workers. It is fine to report on the emotional labor of female domestic workers and yet not do anything about the difficult working scenarios experienced by female domestic workers. The difficult work conditions remain unchallenged. The studies published in academic journals do nothing to mitigate the hardships. I argue that the social sciences continue to reproduce the marginalization of the margins by carrying out work that is distant, removed, and opportunistic.


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