In defense of description

John Gerring has a new article in the British Journal of Political Science [ungated here]which attempts to restore description to its rightful place as a respectful occupation for political scientists. Description has indeed been relegated to the sidelines at the expense of causal inference during the last 50 years, and Gerring does a great job in explaining why this is wrong. But he also points out why description is inherently more difficult than causal analysis: 

‘Descriptive inference, by contrast, is centred on a judgment about what is important, substantively speaking, and how to describe it. To describe something is to assert its ultimate value. Not surprisingly, judgments about matters of substantive rationality are usually more contested than judgments about matters of instrumental rationality, and this offers an important clue to the predicament of descriptive inference.’ (p.740)

Required reading.

Inspiring scientific concepts

EDGE asks 159 selected intellectuals What scientific concept would improve everybody’s cognitive toolkit?

You are welcome to read the individual contributions which range from a paragraph to a short essay here. Many of the entries are truly inspiring but I see little synergy of bringing 159 of them together. Like in a group photo of beauty pageant contenders, the total appeal of the group photo is less than sum of the individual attractiveness of its subjects.

But to my point: It is remarkable that so many of the answers (on my count, in excess of 30) deal, more or less directly, with causal inference. What is even more remarkable is that most of the concepts and ideas about causal inference mentioned by the worlds’ intellectual jet-set (no offense to those left out) are anything but new. Many of the ideas can be traced back to Popper’s The Logic of Scientific Discovery (1934) and Ronald Fisher’s The Design of Experiments (1935). So what is most remarkable of all is how long it takes for these ideas to sink-in and diffuse in society.

Several posts focus on the Popperian requirement for falsifiability (Howard Gardner, Tania Lombrozo) and skeptical empiricism more generally (Gerald Holton). The scientific method is further evoked by Richard Dawkins on the double-blind control experiment (see also Roger Schank), Brian Knutson on replicability, and Kevin Kelly the virtues of negative results. Mark Henderson advocates the use of the scientific method outside science (e.g. policy) – a plea that strikes a chord with this blog.

A significant sample of contributions relate to probability (Seth Lloyd, John Allen Paulos, Charles Seife), and the difficulties humans have in understanding risk, uncertainty and probabilities (Antony Garrett, Gerd Gigerenzer, Lawrence M. Krauss, Carlo Rovelli, Keith Devlin, Mahzarin Banaji, David Pizarro). W. Daniel Hillis and Kevin Devlin mention possibility spaces and base rates respectively as concepts that might help.

Several authors warn of the dangers of anecdotal data (Susan Fiske, Robert Sapolsky) and Christine Finn insists that the absence of evidence is not evidence of absence. Susan Blackmore reminds that correlation is not a cause and Diane Halpern critiques the cult of statistical significance.  Beatrice Golomb discusses misinterpretations of the placebo effect.

You do want to check out some innovative approaches to causality – causation as an information flow (David Dalrymple), nexus causality (John Tooby) and Rebecca Newberger Goldstein’s  ‘best explanation‘ that go beyond the “monocausalitis” disease identified by Ernst Poppel (related argument by Nigel Goldenfeld).

Some highlights from the remaining posts:

- Richard Thaler compares the economic concept of utility to  aether.

- Eric R. Weinstein on kayfabe (!) – the fabricated competition in professional wrestling and… the study of economics

- Fiery Cushman on confabulation (“Guessing at plausible explanations for our behavior, and then regarding those guesses as introspective certainties”)

- Joshua D. Greene on  supervenience (“The Set A properties supervene on the Set B properties if and only if no two things can differ in their A properties without also differing in their B properties””)

- Stephen M. Kosslyn  on constraint satisfaction as a decision mechanism

And Andrian Kreye mentions  free jazz: