Martin et al.: "Strength of Discourse Context as a Determinant of the Subordinate Bias Effect" (1999)

As an argument in favor of selective-access over multiple-access views of ambiguity resolution, this paper provides evidence that the dominant meaning of a word may be eliminated from consideration if prior discourse is biased strongly enough.

In this way, Martin, Vu, Kellas, and Metcalf add yet another chapter to their already somewhat protracted and repetitive discussion with Binder and Rayner.

Tasks and Materials

The authors used two different methods to make their point: Self-paced reading and a naming task.

The naming task consists in reading a word aloud as fast as possible after having read a sentence. It thus allows one to measure priming effects from the sentence to the probe word.

The materials consisted in four different types of sentence, categorized on the basis of human offline judgments of bias. The categories, with examples, are:

1. Strongly favors the dominant meaning of a term:
   The navigator dropped the compass. He searched the deck beneath his life boat.
2. Strongly favors the subordinate meaning of a term:
   The gambler wanted an ace. He searched the deck for the marked cards.
3. Weakly favors the dominant meaning of a term:
   The mother was in a hurry. She jammed the key while opening the door.
4. Weakly favors the subordinate meaning of a term:
   The author was clumsy. She jammed the key while finishing the document.

Remember that the judges only took context preceding the target word into account for categorization. Disambiguating cues appearing later in the sentence were ignored.

As the examples indicate, the authors used two sentences per word, and both in the same strength category. I don't know why they didn't include four different sentences for each word; that would seem to be a more safe methodological bet.

Results

As indicated above, the result of the self-paced reading experiment was that the subjects spend the most time looking at words in subordinate when they occur in weakly biased sentences; in all other conditions, they were faster.

In absolute terms, the differences are not large. In the "easy" conditions, the subjects looked at the target words for about 345 ms on average. In the "hard" conditions, they looked at them for about 370 ms.

The difference is thus on the order of 25 ms or 7% additional looking time. Given the large number of subjects and trials, these effects are significant, but we're not talking about days and weeks here.

Some Quotes

Martin et al. present their own "context-sensitive model" as follows:

According to the context-sensitive model of ambiguity resolution (cf. Kellas, Paul, Martin, & Simpson, 1991; Paul et al., 1992; Simpson, 1994; Vu et al., 1998a, b) either meaning frequency or biasing context can dominate the resolution process dependent upon a third critical variable of contextual strength (i.e. the degree of constraint that context places on an ambiguous word). The bias of a context towards an ambiguous word can vary continuously, from weakly through strongly biased, as a function of the strength of constraints (e.g. syntax, semantics, pragmatics) that converge on the ambiguity. On the weak end of the continuum, word frequency information will dominate meaning computation, but at the opposite end strong contextual constraints will drive the computation process. For example, in the sentence Yesterday, the BANK [was eroded by the heavy rain], the context preceding bank does not sufficiently bias either sense of the homonym (i.e. financial institution or river). Consequently, meaning frequency dominates and the money sense of bank is the preferred interpretation. Consider, however, the sentence The heavy rain eroded the BANK yesterday. In this example, the context preceding bank strongly biases the river sense of the ambiguous word. (p. 815; emphases in original)

This is to be contrasted with a "reordered-access model" in which "all meanings are accessed in all contexts in order of meaning frequency," but in which the subordinate meanings can be moved up the ladder towards the dominant meaning, although not above them (cf. pp 814–15).

What's the Difference?

Both Binder and Rayner and Martin et al. seem to agree that the "reordered-access model" awards a higher weight to meaning frequencies than to contextual fit. They also seem to agree that the "context-sensitive model" does the opposite, or perhaps that it gives equal weight to these two statistics.

I don't see why that's necessarily the case; as described above, the reordered-access model amounts to nothing more than a search strategy — in particular, it does not specify a scoring function.

On the other hand, the context-sensitive model seems to be an informal description of a Bayesian inference. As such, it is perfectly consistent with the greedy search strategy postulated by "reordered access model," or with any other search strategy you desire.

I thus find it a little difficult to get my pulse up over this discussion. As long as the two models are as mathematically underspecified as they currently are, it seems to me that any prediction could be consistent with, or inconsistent with, either model. If the competing parties really wanted to flesh out their claims about the relative weights of priors and likelihoods, they should start picking some numbers.

Another way of putting the same point is that if these researchers really thought that they postulated different weights on priors and likelihoods, then they should also be able to agree on a sentence for which the two models would predict not only different reading times, but also different interpretations.

If no such sentences exists, the difference must solely pertain to the search strategy, and the context-sensitive model does not seem to specify any particular algorithm for this purpose.