Metaphors, analogies, thought mappings

Roald Hoffmann has a fine essay in the recent American Scientist on metaphors, which he describes at one point as “thought mappings.”

Hoffmann suggests that metaphors may be at times useful for (1) explaining technical results to a general audience and (2) achieving and understanding technical results.

In my work, the thought mapping “data graphics should operate at the same resolution as typography” (more generally: data graphics ~ words) was most helpful in creating and justifying sparklines. This mapping provided direct advice about the design of data graphics, and it also had a sustained quality since it carried through to ideas that sparklines could appear wherever words (and numbers) appear and that paragraphs of sparklines should be constructed. There is certainly something of an after-the-fact quality to some of this, and the mapping (data graphic ~word) has its rhetorical as well as technical value in writing about sparklines.

Of course loose or strained metaphors notoriously produce loose thinking. “When a precise narrowly focused technical idea becomes metaphor and sprawls globally, its credibility must be earned afresh locally by means of specific evidence demonstrating the relevance and explanatory power of the idea in its new application. It is not enough for presenters to make ever-bolder puns, as meaning drifts into duplicity. Something has to be explained.” (Beautiful Evidence, p. 151).

A good way for contributors to develop this thread would be to provide examples of specific metaphors that work in the sense that they have some explanatory power. Merely descriptive metaphors–such as the “tree of life” in evolution or the “hockey stick” in global warming time-series or, for that matter, “sparklines”–do not deepen substantive technical thought. Indeed descriptive metaphors may impede such thought. So let us look for some good explanatory metaphors. There needs to be some precision here lest all thought simply becomes defined as thought mappings.