Data

S. Scott Graham, University of Texas

Opening Remarks

Scholarship in the rhetoric of health and medicine has a lot to say about data. A frequent starting point is the rejection of the idea that a datum speaks for itself. RHM recognizes that data are constructed and made to speak in discursive and political regimes. Indeed, to construct and/or to marshal data for use in is essentially to simultaneously invoke the four major stases—fact, value, definition, and jurisdiction. In my work on medical imagining, I (2015) have tried to show how MRIs and PET scanners are basically engines for serving data about what is taken for medical ground truth from the messy subjectivities of a patient’s life. As imaging data are constructed, facts are separated from non-fact; different modes of evidence are valued and de-valued; evidentiary jurisdictions are established; and diseases are defined. The simultaneity of stases in dispute is perhaps best showcased in Crista Teston’s (2017) Bodies in Flux where she explores how different forms of data are contested in tumor boards to establish the medical facts, define the condition, determine subspecialty jurisdiction, and commit to treatment actions.

Now, I would be remiss if I did not also mention what RHM tells us about how medical data regimes are inflected (or perhaps infected) with non-medical value. Judy Segal’s (2015; 2018) account of flibanserin (so-called “female Viagra”) is instructive here. In an amazing rhetorical sleight of hand, one of the primary outcomes used to measure the effectiveness of flibanserin is the extent to which men find sex more enjoyable when their female partners are medicated. Similarly, Raquel Robvais (2020) explores how racism in Western medicine occludes and denies patient narrative data especially when it comes from Black bodies in pain. Her recent POROI article further traces how those with sickle cell anemia must adopt alternative subject positions to render their narrative legible in the data regimes of white, Western Medicine.

Beginning then with what we know about data, my hope today is to catalyze a reflexive conversation. RHM, like medicine itself, is an inquiry tradition. As academics, we are charged with constructing and invoking data so as to better support future action. As we approach biomedical data, we benefit from distance and critical perspective, and that allows us to think richly about the rhetoric, ontology, and politics of data. However, within our own disciplinary spaces, our conversations about our data are not always so nuanced. It’s harder to adopt a critical perspective reflexively. This conversation is also challenged by some in RHM who argue that our evidence is not data. So, even if that’s your approach, for this exercise in reflexivity, I’m going to ask you to consider what it might mean to think about our evidence as data. As we do, I’ve generated four questions to serve as chum for our conversation. Lisa has posted these online, but I’ll read them quickly if you don’t have them at hand.

  1. What counts as data for rhetoric of health and medicine?
  2. How do our inquiry practices create/construct/constitute data?
  3. What are our data stases? What do our data construction/invocation practices say about our approach to fact, value, definition, and jurisdiction?
  4. What new forms of data or new approaches to constructing data might help us better disrupt unjust ideologies and systems?
References

Graham, S. S. (2015). The politics of pain medicine: A rhetorical-ontological inquiry. University of Chicago Press.

Robvais, R. M. (2020). We are No Longer Invisible. Poroi, 15(1), 6.

Segal, J. Z. (2015). The rhetoric of female sexual dysfunction: faux feminism and the FDA. CMAJ, 187(12), 915-916.

Segal, J. Z. (2018). Sex, drugs, and rhetoric: The case of flibanserin for ‘female sexual dysfunction’. Social studies of science, 48(4), 459-482.

Teston, C. (2017). Bodies in flux: Scientific methods for negotiating medical uncertainty. University of Chicago Press.

Synthesis from Breakout and Discussion

Running Definition
    • The scholarship in the rhetoric of health and medicine has a lot to say about data. A frequent starting point is the rejection of the idea that a datum can speak for itself, or recognize that data are constructed and made to speak in discursive and political regimes. To construct and or to marshal data for use is essentially to simultaneously invoke the four major stases: fact, value, definition, and jurisdiction. Data can catalyze a reflexive conversation, and that’s one of the goals of it. Since medicine itself is an inquiry, us academics are charged with constructing and invoking data, so as to better support future action. So this conversation is also challenged by the fact that some in RHM will argue that our evidence is not data. So how we keep defining data and its roles in our work is imperative.
Takeaways
  • Within our own disciplinary spaces our conversations about our data are not always so nuanced because it is harder to adopt a critical perspective reflexively.
  • We need to attune to who is reinscribed and why. Rationale: when we as scholars make nice little transcriptions we miss stuff, and this may opens the possibilities of how “perfected” transcripts may miss the points; they may miss the deeper meaning that is so important.
  • The field methods turn to some areas of rhetoric that there are some things that we want to study that have not been inscribed, or were/not inscribed for other purposes and so it becomes important that we find a way to inscribe them for ourselves.
  • As RHM scholars, we need to double down on reflexivity and transparency to consider the limitations of our work and what may be excluded by our data collections. This will help our articles about what we’re studying and why while attuning to what information or phenomena may have been occluded.
    • Without this move, some of evidence can hurt the field as there is a recurrent issue of our evidence being policed by other disciplines for not being sufficient data.
  • The primacy of data provides a good reason to challenge data as a way of describing evidence.
Future Considerations
  • Continua of interest – who does the inscribing? Tradition rhetoric usually finds data that has already been inscribed (by others for other purposes).
  • One reason for the turn in methods in RHM is that there are some things that haven’t been inscribed so we need to find a way to inscribe them for ourselves.
  • Reflexivity and transparency – room to double down on them more. We need to.c
    • Limits and treatment processes are important.
    • What can we say more about in our research that helps us?
  • Should we even be saying that our data is “evidence?”
    • Our field can be policed for not being sufficient as not real – that challenges our modes of data as saying they’re evidenced.