Tag Archives: rhetoric of science

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Awash in Dubious Metrics

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Nationwide polls for the 2016 Republican Party presidential primaries.svg wikipedia.org

Language has a kind of expressive power that numbers cannot match. So why has so much of our research in the humanities and social sciences spurned verbal description in favor of numerical measures?

Humans are a diverse lot. Even so, research conventions dictate that explorations of the many facets of the human condition should now be represented in numbers: usually percentages, raw totals, averages, or deviations from the average on single or multiple scales. Variables are identified only if they can be operationalized and counted in some way. And while these numerical summations will sometimes give us a useful “big picture” view, they frequently distract us from seeing the enormous multiplicity that exists within human groups. This is heresy against current orthodoxy.  But hear me out.

In my own field of communication such analyses sometimes gain a thin and partly unearned patina of rigor and exactitude. Speaking broadly, they can easily become fraudulent when they are meant to represent complex internal states: for example, levels of empathy, degrees of emotion or sympathy, or when even when representing acceptance of a thing, person, or idea.  Should we be surprised that even something as straightforward as political polling is noticeably unreliable?

Governments, organizations, and publishers love “data.” Data sets are almost a prerequisite for any claim of academic seriousness. They appear to be  unassailable. Dissertation advisors routinely steer their students to work up pages of numerical summaries that may say little about the uniqueness of individual cases. Tables, scales and percentages buy a degree of credibility. As the misplaced aphorism goes, “numbers don’t lie.” But of course they do.  The appearance of a precise numerical measurement is probably the most important trope in the rhetoric of the social sciences, even when an individual measure would be more useful “opened up” with illuminating descriptions or representational stories.

Goffman wikipedia
               Goffman 

Older and more discursive modes using ordinary language were once favored by an impressive group of mid-century thinkers systematically exploring cultural and individual markers. Among many others, Erving Goffman, Kenneth Burke, George Herbert Mead, and David Reisman enabled landmark advances in the humanities and social sciences. Their of use of dense description to explore underlying patterns of language usage and behavior sustained a broad range of explorations for many. As one modest scholar captivated by their probes, I could barely work fast enough to keep up with just a few of the their intellectual pathways. Their discursive modes of writing invited explorations of useful ambiguities, exceptions, and insights triggered by illuminating metaphors.

It is interesting to note that specificity of description is how narrative in all forms treats social issues. As the sociologist and rhetorician Hugh Dalziel Duncan noted, drama allows us to be “objects to ourselves.” But it should not fall only to the dramatist to witness and report another’s lived experience. Modern scholarship often needs the specificity of an individual case. One advantage is that a single study can explore an individual’s perceptions. Since these forms of awareness can vary across a population, they do the honor of treating a subject on their own terms.

Single or limited cases can also illuminate patterns evident in a portion of an entire class. Alexandra Robbins’ recent book focusing on a handful of elementary school educators (The Teachers, 2023) is surely more illuminating about current challenges in our public schools than a lot of the opaque data published every year.

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Language is expressive; numbers are not.

I encountered the useless and diminished value of numbers in a study I completed several years ago that looked broadly at sound and hearing (The Sonic Imperative, 2021) The capacity to hear requires a broader range of reference points than with other kinds of projects. Sound has its own physics, which can be represented in units of volume (decibels) or pitch (frequency). But when looking at human perceptions of sound, we must consider individual and unique variations. The gateways to every human mind are distinctive. So, our perceptions of sound, or food, or images must bend to the subject. Even while we have acquired metrics that identify many features of a person, sensory complexity is best approached phenomenologically: as experiences we can explore, but are rightly owned by the individual.

Returning to the case of sound, we surely need the precision of acousticians, engineers and others who measure and document patterns and boundaries of auditory content. We have the tools and electronic instruments to make sound discussable. And in musical notation we also have an awkward but functional way to visually represent the ephemeral artifacts of organized sounds. But a copy of a musical score is not what passes through the ear. If we want to say more about that process, we all must be phenomenologists, applying a range of descriptive forms: self-reports, dense descriptions of others, and the judgments of academic critics who have devoted their lives to appreciating what we may not notice.

To cite a specific case, some researchers have tried to measure and set out gradations of the human response of empathy, which can be triggered by an image, sound, or a simple conversation. But using metrics to describe so personal an effect is a fool’s errand. We have better tools on display in the seminal works of many cultural critics. Academia would frequently do well to give more credibility to these adequately curated impressions, resisting the urge to flatten every idea into a one-dimensional category that can be numerically expressed. Language is expressive; numbers are not. Like music on the page, numerical tallies of all sorts are mostly dead on arrival until they can be converted back into the living form they are only meant to approximate.

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The Deterministic Mind

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Wikimedia Commons
                                      Wikimedia Commons

In our narratives about how our  world works we lean heavily on the idea of cause-and-effect predictability.  But a causation slot that must be filled in makes the world seem more knowable than it really is.

In his book How The Mind Works (1997) psychologist Stephen Pinker notes that the very idea of science assumes that there are direct causes for any material effect. Ask an experimental psychologist about the nature of a particular behavior, and the conversation will eventually drift toward its possible social or familial roots.  Look at research on urban gangs, and the talk will soon include the contributing forces of peer and environmental factors.  The social and hard sciences are generally in the business of seeking first causes. They need this conceit in order to work.  To be sure, we are often better off because of their efforts, but not always.

For most of us this science template has probably infused itself in the ways we make sense of the everyday world.  Looking for causal chains seems like the very definition of mental rigor.

From this perspective cataloguing effects is not enough. For example, uniform crime reports are interesting, but only get us so far. Our accounts for how the world works is anchored in our faith that things can only get better when causes are revealed and controlled. After all, events without apparent causes are disorienting.  A tree that falls and kills a passerby tests out willingness to accept seemingly random events with lasting consequences.  We want to know why, and how to control conditions that can prevent such deadly events.

Even with this natural impulse, we overuse the template.  A causation slot that must be filled in makes the world seem more knowable than it actually is. We cherish lexicons of determinism. For example, we easily classify people into personality types, where the labels (“neurotic”, “needy,” “depressed,” “obsessive,” to name a few) become concrete explanations for behaviors tied to personality traits.  But why Aunt Millie has a personality disorder is still anyone’s guess. Similarly, when a plane falls out of the sky we resort to the same template for making sense of what has happened.  When we ask “what went wrong?” we expect a precipitating cause to be named.  Only later do accident investigations usually reveal multiple problems that combined to create a disaster.

In our rushed and over-communicated age we rely heavily on the simplistic and deterministic. 

Consider a different kind of example. Imagine if you are a neuroscientist. How long can you retain your professional credibility if you take the risk of  acknowledging that the mind is partly “unknowable?”  Neuroscientist’s study the brain and generally shun discussion of the “mind,” the useful label for what the brain has given its owner by way of a wealth of experiences and perceptions.  What I see in my ‘mind’s eye’ is likely not what others see.  But how do we find the causes for those mindful thoughts?  A brain scan won’t cut it.  Consciousness can’t be reduced to predictable neural pathways. And so the idea of mind muddies the scientific impulse for the measurement of particular effects.  Thus the brain sciences generally remain silent on this rich idea, preferring to study the organ of thought more than thought itself.

This kind of problem is why the search for first causes tends to force us toward the absurdly technical or the overly simplistic.  On the simplistic side, compressed ideas about why things happen indeed yield answers:  usually good enough to see us to the end of the day, but not very reliable as bases for creating lasting understandings. The shorthand vocabulary of causes that we inevitably use give us dubious deterministic links that we nonetheless cling to.  And so Muslims cause terrorism, African-American males are dangerous to be around, and politicians are corruptible.  Each labeled category is pushed next to an arrow that points to a list of supposed causes, producing “answers” that in their narrowness are hardly worth knowing.

Sometimes the best response in reply to an unfolding set of events is uncertainly.  Even with the need for simplicity in our busy lives, we have to save room to let in the messiness that is part of the human condition.  Instead of imagining arrows, we need to think of webs.  A web is a better representation of lines influence that are complex and pass through rooms of intermediate and unknown causes.  If we want to be a little smarter all that is required is the resolve to give up the short-term thrills of unearned certainty.