“Any story differs with each passing moment, new purpose, and favored vantage point. Neither the whole story nor the true one ever exists, however much we may wish for it. If we could achieve wholeness and absolute truth in our stories, we would have no more stories to tell. And tell stories, we must.”
–Shirley Brice Heath, Words at Work and Play
The first part of this essay was concerned with data that purports to be objective, but really isn’t. All of which raises an obvious question: how can we make our data more objective?
Speaking as an anthropologist, I’ve got some bad news for you: we can’t. It’s not possible to observe human behavior from no vantage point at all. And I would go a step further and say that we shouldn’t try to.
Objectivity and Positionality
You’ve probably heard of the observer’s paradox (sometimes called the observer effect): the act of observation changes what’s being observed. It’s true of the physical world, and it’s certainly true where people are concerned.
Anthropologists have several ways of dealing with this. Most importantly, we make ourselves a constant presence. If we’re audio- or video-recording, we use the equipment much more than is strictly necessary. Why? So people will forget that we’re there, as much as possible, and behave less and less like they’re being observed. (We could, perhaps, observe people without letting them know that we’re doing it, but it would raise some huge ethical issues to do so.)
And the truth is, observation is part of our very object of study — social interaction. (I don’t know any linguistic anthropologists who look at people talking to themselves!)
It’s not only the act of observing that changes what is observed; who’s doing the observing also has an effect. As a result, we anthropologists spend a lot of time talking about positionality, or the recognition of where the observer is situated.
Imagine you’re at a stadium, watching your favorite sport. Your team scores an amazing goal — and the referee says it doesn’t count. Do you continue to insist that the goal was the best you’ve ever seen, or do you accept that the referee saw something you missed?
That’s what positionality is all about. It’s a recognition that your vantage point changes what you observe. There’s a physical component to it, as described above, but there’s also a social component. Race, gender, ethnicity, group membership, and all kinds of other social identities play a role.
Let me give you an example. I conducted research with indigenous Mexican Jehovah’s Witnesses for the better part of a year. Here’s a non-exhaustive list of things about me that affected the data I collected:
- I speak Spanish very well: I was able to ask detailed questions and understand the nuances of the answers.
- I’m White and relatively well-to-do, but not Mexican: indigenous communities tend to be distrustful of well-to-do Mexicans for historical reasons.
- I dressed conservatively: in doing so, I communicated that I shared values with the Witnesses I spent time with.
- I’m a woman, and a fairly young one: I was able to spend time alone with women without arousing suspicion.
- I was introduced to the community by an archaeologist who had worked there for 10 years: I had been vouched for, which made people more trusting.
- I’m not a Witness: because converting outsiders is central to Witnesses’ religious practice, people went out of their way to talk to me and to answer any questions I had about the religion.
Some of these things were completely beyond my control, while others were fully within it. And I could never hope to write a fully complete version of this list — our reactions to other people always depend on dozens of factors, and we may not ever be aware of all of them. We can, however, address some of the most important ones.
Onward to Transparency
Instead of aiming for the impossible ideal of objectivity, we should reach for something we absolutely can attain: transparency.
What does it mean for data to be transparent? It means frank discussion of how we got our data.
For qualitative research, it means reflecting on our positionality and discussing it. Who am I? What’s my relationship with this community? How did I present myself? What role did I play? What kinds of data would a different person have gotten that I didn’t, or couldn’t?
For quantitative research, it means discussing how we operationalized the things we think we’re studying. How were those test questions written? How well do they correspond with other measures that supposedly quantify the same thing? Provide the wording of your survey questions. And so on.
Matt LeMay has written that the word “data” is a smokescreen. I echo his call for transparency around methodology, and particularly around the assumptions and identities that color all of our work.