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Arguing Cause, Correlation, and Effect

Page history last edited by ShareRiff 13 years, 5 months ago

Arguing correlation, cause, and effect

keyword: "because"

Epigraph

"Historically medicine has searched for a single causal agent such as a molecular abnormality, a virus, or a defect in a gene as the etiology of any particular disease. Similarly we tend to think of a specific risk factor as being associated with a particular disease. Consequently the discovery of a single risk factor associated with the widest spectrum of disorders is strong evidence of some underlying connecting phenomenon of disease and health that we have not yet understood"

-"The Origin of Disease and Health Heart Waves: the Single Solution to Heart Rate Variability and Ischemic Preconditioning," by Irving Dardik

Rationale:

Our world is tightly woven, and causal arguments abound. For example:

Violence on television causes people to commit crimes

Statements of cause and effect are helpful when Writing to Evaluate because they help us articulate values, define the scope of a problem, and identify avenues that our audience can programmatically pursue in order to a problem or area in need of innovation.

Invention:

When we experiment with causal claims, we can try recasting them into the form of a question, which we can then proceed to answer in our writing. This example also shifts the context slightly, and considers video games as an agent of causality:

Does playing violent video games cause violent and aggressive behavior?

Here, the author immediately makes a distinction between cause and correlation, and cites studies that come to different conclusions.

In fact, in most cases, one can easily find alternative and multiple causal claims. Therefore, while causal claims come easy, it is difficult to sustain a causal argument that has real stakes, because a simple and quick reversal is all it takes to render a counter claim. So, the mode of anticipation we have come to know as prolepsis, definitional and evaluative heuristics, and narratival strategies come in handy when we seek to develop supportive reasoning for causal claims, and render them into substantial causal arguments. Testing counterarguments--recursively revising enthymemes--also helps us find out who really cares about an issue, so we can tune arguments to what's most important to discuss. Otherwise, lurking variables may haunt your case.

After looking for causal arguments in the field and testing them in different communities, it might be a good idea to back up a little bit, and slightly soften your causal argument in-the-making. One way to do this: simply assert a correlation between 2 things. Try "playing violent video games correlates to high test scores," or any claim taking this sort of form, and then submit that assertion to a series of questions designed to test for different kinds of cause and effect relationships.