How do we choose to understand “data” in times of rising fascism?

As new forms of fascism are on the rise, we regularly hear of fake news in relation to Trump as well as other conservationist and fascist voices. So, what is the relation of fascism and fake news and how do we collectively choose our notions of “data” and “factfulness” during those times where they seem to be a political warzone of sorts?

During the panel “Considering and Contesting Data” four empirical researchers present their data as well as how they conduct it, and how data is in fact shaped by choices of scope, methods, categorization, etc. This guides us into a deeply interdisciplinary conversation that essentially implies a question that sounds as simple as it is in fact complicated: What is data?

During my PhD defence I deeply unsettled one of my committee members: I have conducted philosophical research on mathematics that is incredibly problematizing in relation to notions of “proof” and “evidence” that have largely been constructed from within white and male-centric logic. Said committee member however seems to (from what I understand) wish for a kind of “factfulness” that combats fascism. She seems unsettled by how deeply I call this notion into question because she is concerned about how we can fight the fake news and misinformation fascism strives off if decolonial-feminist politics seem to guide us far away from an idea of “hard factfulness” that combats fake news.

I am reminded of this part of my defence as I listen to this Sexploration panel - the experiences, thoughts, methodologies and shared conversations between the researchers in this event guide me into this very tension again. Because they confirm what I have said in my defence:

Data is not fiction, but nor is it some sort of hard fact that is bestowed onto us straight out of the platonic heavens. It is a construction in the complicated meaning of the world, where a construct is always more-than fiction: data is created through research and research is a process of making.

One of the researchers in this panel explores queer youth and they share a striking example on how measuring is creating - not as in “inventing”, but as in co-creating the result: They share a multiple-choice form where people are asked to select their age and only very particular ages or age ranges are named. Therefore, most people filling out this form would not be able to accurately choose and still, the form would - of course - create data.

A crucial part of her work is to highlight how this is precisely how gender is often measured in empirical research. So, historically and contemporarily empirical data has been created through measures that are likely to create particularities, biases, and invisibilities in relation to gender and thus relations gender holds to a variety of topics and issues.

Other researchers chime in to affirm that as researchers they choose a scope, an objective, a narrative, a method - all of which are creational choices!

So, what can all of this mean in a world where fascism strives off of misinformation? What do we have to give for the anti-fascist struggle when it comes to knowledge and its making?

I do not have any answers, but I can share where my questions have led this far:

Fascism strives off of fake news, yes. But this does not automatically mean it strives because people believe fake news. What it often means is something quite different: fake news support a world in which people do not know what to believe anymore and where to put their trust. This is different!

And what about the aspect of data being something that is created? It makes it non-platonic, not from the world of “hard facts” that some are craving. But it also does not make data any sort of irrelevant or untrustworthy. If we dare to look, this situation can make us ask the kinds of questions that will help bring trust, solidarity, and collective knowledge-making that is fiercely against fascist gaslighting without needing to dream of platonic neutrality. 

A world, in which fake news that distort the false-true distinction, causes mass confusion and political vulnerability, is a world that suffered from a lack of epistemic (knowledge-related) nuance in the first place: there has always been more than truth and falsity and those have always been part of how we perceive, see, measure. 

So, if data is not our platonic saviour, it might first and foremost mean that we do not require that kind of saving, but actually choiceful nuance:

What someone like my committee member is likely afraid of is a sort of randomness that fascism and misinformation can benefit off of. But what I am putting forth is to listen to people who conduct data and learn nuance with them and from their reflections:

Measuring is a creational act and the better we understand the choices and dynamics that go into this creation the more nuanced and choiceful we can be about how we understand data and knowledge. And the more confident we can be that we will not require one answer, one definition, but rather a courage to look, to speak, to listen, to create knowledge and knowledge-making together, and to differentiate. 

It is when we grow deeper and more collective than a true-false binary allows that we will combat fascism. Fascism dies when simultaneity is demanded because it requires people to be confused instead of fierce in messiness - so let us do that, growing fierce and confident in the messiness that knowledge-making always is. Not all knowledge and knowledge-making is the same, but they are not simply distinguished by truth and falsity - so let’s go deeper and let’s not be afraid of the depth.