Whenever I get into these correlation and causation battles (and I do frequently, both in the university and online), they seem to go wrong in two ways: one, people often insist on an entirely unhelpful definition of the word “implies,” and two, people often presume some quantitative signifier of absolute causation that does not exist in most fields.
For the first case, there’s a widespread and strange contention that “implies” is synonymous with “proves.” I find this out of character with conventional use: the word implies seems to exist specifically to indicate a softer claim that the word proves. “Officer, did the suspect specifically state that he wanted to buy drugs?” “No, your honor, but he implied it.” My boss implied I would get fired if I didn’t do my work. The woman at the bar implied she’d like me to buy her a drink. Etc etc. To say that an implication amounts to proof positive just seems contrary to the way we use that term, to me. If you’d prefer “suggests” or “provides evidence for,” then I’ll use that instead. But in each case, we are make a probabilistic judgement call, not a simple quantitative conclusion, because of point two: in the large majority of fields, causation is a philosophical, epistemological concept, not a mathematical one. In those fields where there are communal standards of causation, from my limited knowledge, they tend to be beyond the reach of a vast majority of the social sciences.
Take a field where the stakes for research are high indeed: medicine. Robert Koch, a pioneering epidemiologist and physician, proposed four criteria for demonstrating that a particular pathogen caused a disease.
1. the microorganism or other pathogen must be present in all cases of the disease
2. the pathogen can be isolated from the diseased host and grown in pure culture
3. the pathogen from the pure culture must cause the disease when inoculated into a healthy, susceptible laboratory animal
4. the pathogen must be reisolated from the new host and shown to be the same as the originally inoculated pathogen
You can already imagine the host of problems here, even for a field as “hard” as the medical sciences. We know that there are agents in medicine which contribute to diseases or conditions but which are not necessarily present in all cases. (10% of lung cancer victims, for example, have never smoked.) Growing pathogens in cultures is very straightforward if that pathogen is a bacterium, but far less clear when we’re talking about many kinds of environmental and behavioral risk factors. Replicating certain behaviors or conditions in lab animals is often a practical impossibility, and in many instances, human epidemiology varies drastically from that of mice or similar lab animals. Reisolating a causal agent again makes sense if we’re hunting for a bacteria and no sense if we’re asking if exposure to soot causes scrotal cancer. And so on. So eventually, Koch’s requirements had to be discarded in some avenues of medicine such as carcinogenesis; the bar was simply too high, and the need for more cancer science far too great.
In some fields, the only responsible way to assign a cause is through a controlled experiment. That often means that the researchers must themselves control the given exposure or other independent variables, introducing them into the test group themselves. The ethical quandary is obvious: no institutional review board in the world will allow you to deliberately expose a test group of babies to tobacco smoke in hopes of determining strong empirical proof of causation. (I hope!) Similarly, no one could or should divide babies into a cohort to be raised in affluence and a cohort to be raised in poverty for the sake of experimental value, even though we might learn more in doing so that we have in decades of educational research. Instead, we are left to muddle through with observational and quasi-experimental designs in which researchers cannot themselves control exposure to a given independent variable, which some serious epistemologists would say is a requirement of truly demonstrating causation. And we do alright, sometimes, if we’re careful, limited in our claims, and we replicate. (With lung cancer, at least, we can see the physiological changes that occur from smoking. How could we ever look for a physiological sign of causation in the brain of an impoverished child struggling to succeed in school? Where would we look?)
So I will again go out on this limb: I believe that poverty causes poor educational outcomes. I think by a rational, fair standard of what we mean in common human language by a cause, that statement is true. The evidence? Decade upon decade of studies that demonstrate a strong correlation between the socioeconomic class of students (or their parents) and educational outcomes. Across a broad variety of contexts, for a number of different age groups, in all manner of different levels and types of schools, we see that basic dynamic. I’m not suggesting simplicity here. While I believe poverty is a cause of educational failure, it is surely not the only cause. And while this basic dynamic is present in reams of data, the effect size is not always the same, the effect is not always equally distributed across the income spectrum, the effect sometimes changes according to age cohort, and on and on. Yet I feel confident enough in the relationship I’m describing — and in my readers to understand nuance and appropriate limitation — to say that poverty causes poor educational performance.
If you think that my use of the word “cause” here is problematic, or simply wrong, I’m very happy to have that discussion. The literature on this topic is vast, and I’m nothing resembling an expert. But for practical purposes we have to allow for sufficient linguistic and epistemological simplicity to actually grow the “storehouse of human knowledge.” We might get experts together from a variety of fields to debate and develop fair, pragmatically-useful definitions of cause that are reasonable for those fields. But I find that debate so much less fruitful than many other forms of inquiry we can undertake if we all agree to understand causation as contingent and complex.
I again recommend The Emperor of All Maladies for a very cogent discussion of how all of this played out in the realm of cancer where, despite being on the forefront of modern science, with incredible resources, the best-trained researchers could not prove causality to Koch’s standard, which the tobacco companies used to nefarious ends. Siddartha Mukherjee writes on page 256, “Rather than fussing about the metaphysical idea about causality (what, in the purest sense, constitutes ’cause’?), [Bradford] Hill changed it to a functional or operational idea. Cause is what cause does, Hill claimed.” If that’s good enough for investigating cancer, it’s good enough for me.
Update: Forgot to mention that this essay by Greg Laden is just terrific on these topics.