Ours is a data-driven era, both within broader American culture, and specifically within higher education. Many faculty members think that administrators are only concerned with numbers, and that they have a tendency, perhaps even a predisposition, to neglect the larger narratives, telling anecdotes, and less quantifiable factors that also measure a college or university or program’s successes. Perhaps many administrators do neglect such things, but we faculty members sometimes enable that neglect through our own distrust of the numbers, and sometimes through our own innumeracy.
We can whine all we want that administrators are too number-based in making many of the decisions that govern how universities operate. There may even be a good case that we are too deferential to such numerically driven decision-making within the modern academy. But in the short term, that situation is not changing. Rather than bemoan the “data-driven” state of affairs, and perhaps while working against it when appropriate, individual professors, and particularly those with any administrative responsibilities, need to become more savvy readers and users of numerical data. If you work for a university of any size, your institution collects an absolutely breathtaking amount of data on students, classes, programs, on virtually every measurable angle of university operations.
Ignoring this data, which is usually free for the asking within our home institutions, or failing to learn how to navigate the data and deploy it within your own institutions, could be a terrible mistake. In dramatic cases, such neglect might allow others to “control the narrative” regarding programs and decisions that are important to us and our departments. In less dramatic cases, failing to examine the existing data that is relevant to us and our departments may prevent us from making the best decisions regarding degree programs or class offerings, may simply blind us to important details about our own programs and initiatives. When engaged in policy debates, innumeracy, and inability to understand the numerical data, has the potential to discredit our arguments, or causes us to misunderstand the arguments of others.
Sociologist Joel Best, who has devoted much of his career to explaining what I would describe as the “rhetorical function of numbers,” is the author of several books on the role of statistics within knowledge-building. I have frequently used one of these books, Damned Lies and Statistics, within my undergraduate classes. As Best points out, “People use statistics to support particular points of view, and it is naïve to simply accept numbers as accurate, without examining who is using them and why.” Too often we are deferential to the numbers we encounter, and fail to offer our own numerical data or interpretations of numerical data within university decision-making.
I should point out — I don’t teach math, and I’m not a sociologist. In fact, I teach something that is frequently, though quite wrongly, presented as the counter-math, something often wrongly assumed to have nothing to do with numeracy. I teach rhetoric and writing. And within my undergraduate writing classes I have frequently used Best’s book as part of a larger argument of mine to students that numeracy, the ability to understand numbers and statistics, is an important component of contemporary literacy. As my administrative responsibilities increase, I see also that many of us faculty members could benefit from a similar reminder, or education, on how numbers function, not only mathematically, but also rhetorically.
Innumeracy, the inability to comprehend the meanings and implications of numerical data, is not always the problem. Simply being numerate, or understanding how it is that numbers and statistics function, how they are derived, and what they represent within a larger context is not enough.
An even greater problem than innumeracy, I believe, is when those who do understand statistics, how they are derived, and what they represent, too often neglect to consider the rhetorical function of numbers, or perhaps assume that numbers are self-representative and “speak for themselves.” Numbers never speak for themselves. Like language, numbers are always subject to interpretation, and we ought not accept them uncritically.
And within the modern academy, numbers swirl constantly around us. The intricacies of how to access and deploy things like academic reporting software are one of the many, perhaps seemingly pedestrian, skills that are not often taught during graduate training, but are essential to leading a productive, successful career, particularly in terms of conducting advocacy within one’s home institution. I, for one, never realized when I became a teacher of writing just how largely spreadsheet software and arcane, often user-unfriendly academic reporting software would factor into my professional life.
A couple of questions to consider when deploying or encountering numbers within our institutions might include:
- What are you trying to achieve by presenting numbers? Do the numbers actually further that cause?
- Do you trust the source of your numbers? Will your audience?
- Do the numbers you have generated accurately reflect the larger context? Or does that context need to be provided for audiences?
- Are there alternative ways that your audience might interpret your numbers? Are those alternative readings reasonable and responsible? In any case, how might your respond to alternative readings of your numerical data? Do harmful readings of your numbers need to be “headed off at the pass,” and such counter-readings debunked as part of your argument or presentation?
- Are there risks in presenting or releasing your data set?
Ours is an extremely number-driven culture. For some reason, many of us suspend our skepticism when presented with numerical data, particularly if it appears to confirm our existing beliefs. Even worse, many of us have unintentionally bought into a myth that the deployment and interpretation of numbers is the exclusive purview of a segment of math-whiz specialists. We are the inheritors of a pernicious false dichotomy that pits humanistic intelligence against scientific intelligence, as if those two things are even so separable, so discreet.
We see this dichotomy perpetuated in our students when they claim to be terrible at math, but good at English, or good at writing, but incapable of algebra. It’s as if there is some cognitive zero-sum game wherein one may only be competent in one area of thinking, but not others. Perhaps no place is this more obvious amongst ourselves and our colleagues than when it comes to dealing with numbers, and how we deal with them.
I frequently hear faculty members make pleas similar to the ones of our students. “Ah, I’m a writer, not a numbers guy,” one protests. “I can’t write, so let me crunch the data,” another pleas. It’s time to call BS on these protestations of ignorance. Successful scientists are deft, clever readers and writers, nimble in the world of words and language. Similarly, capable humanists are as savvy at reading, interpreting, and critiquing numbers as they are any other texts.
Numbers, while they can be objectively derived, are — like all human signs and speech — ultimately rhetorical, and, as Best so convincingly argues, are socially constructed. That doesn’t mean that numbers are relativistic bunk. But it is to say that numbers have a persuasive force that is no more legitimate or illegitimate than any other utterance of language. We ignore the persuasive capital of numbers at our own peril, whether we are failing to interrogate the numbers we are presented or failing to present the numerical data that might bolster our own advocacy. All of us, in all disciplines, need to be comfortable confronting and deploying numerical data.