Rosch: "Principles of Categorization" (1978)

Elanor Rosch's contribution to Cognition and Categorization really consists of two independent parts: An overview over her experiments investigating basic-level categories (pp. 30-35), and an overview of her experiments with prototype effects (pp. 35-41). In will only deal with the first part now.

Cue Validity

The most central concept in Rosch's discussion of basic-level categories is the notion of the cue validity. This is defined for a category such as "bird," which is more or less reliably identified by cues such as "wings." She explains:

The cue validity of an entire category may be defined as the summation of the cue validities for that category of each of the attributes of the category. (pp. 30-31)

This immediately raises two questions:

1. Do all cues count in the summation with equal weight? There are infinitely many possible cues and only a few highly valid ones. This suggests that more explicit assumptions about "salience" are needed.
2. With what weight do the various members of a category contribute to the average? Equally? Weighted by the frequency of the linguistic label? Weighted by the frequency of the thing?

While these questions may seem like technical remarks, they do in fact relate to some deeper issues that I will mention below.

The Ambiguity of "Basic"

There are two competing characterizations of "basic" in Rosch's work, an ostensive and a perceptual. It's not always clear which one she is taking as definitive, and this sometimes introduces problems.

Both definitions apply to concept trees and are meant to pick out a particular depth in such a tree. They do so by locating the level of abstraction at which either

1. the categories "car," "chair," "tomato," and "hammer" are found; or
2. average cue validity is maximized.

My worry is that her cross-cultural, developmental, and evolutionary claims may turn out to be tautologies when we look closer at the ups and downs of her theory.

For instance, if the "basic" means "maximal cue validity," then of course children learn names from this level first. On the other hand, if Rosch gets to pick what counts as "basic" in each branch of the English category system ("chair," "car," "tomato," ...), then she can obviously just pick the level that fulfills the second definition.

Learned Perception

The fact that she might unknowingly be making the tautological point that "normal things are normal" is hinted at when she comments that English-speakers tend to be less able to distinguish between plants than the ostensive definition suggests.

This is observation was echoed more recently my Jerome Feldman:

For many city dwellers, tree is a basic category—we interact the same way with all trees. But for the professional gardener, tree is definitely a superordinate category (Feldman 2006: 186)

With those kinds of qualifications, basic level categories will certainly guaranteed to have all of the properties that Rosch claims. But any claim about their universal centrality will also become an empty verbalism.

Note how this also ties in with the sticky issue of trained perception:

One influence on how attributes will be defined by humans is clearly the category system already existent in the culture at a given time. This our segmentation of a bird's body such that there is an attribute called "wings" may be influenced not by perceptual factors [...] but also by the fact that at present we already have a cultural and linguistics category called "birds." (p. 29)

She is apparently aware of this problem, but not willing to face the implication that complex cues like plumage are themselves categories that are open-ended and ambiguous.

Mutual Dependence and Iterated Learning

She does note, however, that attributes might be extracted from categories just as well as categories might be based on attributes. However:

Unfortunately, to state the matter in such a way is to provide no clear place at which we can enter the system as analytical scientists. What is the unit with which to start our analysis? (p. 42)

To me, this suggests a game-theoretical analysis. A category system is invented by people, but also has to be transmitted; fixed points in such an iterated learning process will be the systems that trade off difficulty of acquisition for pragmatic necessity, I guess.

This process could probably be modeled relatively easily in a multi-agent system with a set of Bayesian learners. However, such a model will probably be highly sensitive to the assumptions made about the environment of learning (e.g., the frequency of birds and the frequency of winged-ness).