nice tools for preparing stimuli

Creating pseudorandom orders with customized constraints:

Convenient image resizing tool:

Convenient mass renaming tool:

I haven’t explored the full extent of this yet, but this could be amazing for image analysis:

Calculating pixel area or counts: Histogram (uncached by clicking on the exclamation point) or Analysis > Record Measurements

Calibrating your monitor:

Excel function translations:

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categories vs. continua

Sure we love to categorize things and experiences into discrete regions and there’s surprising structure to the physical world, but that doesn’t mean we have no ability to represent the fine-grained subtleties that exist. We don’t lose the gradient information in the distributions (albeit with modes or local peaks); rather, we represent the underlying gradience and often engage in further processes based on discrete categories. In theorizing, scholars too often partition things into rigid categories in a dogmatic way and forget about our flexibility to work with scales in the mind and the world in a probabilistic way.

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graded membership and fuzzy truth

The interpretation of Armstrong, Gleitman, and Gleitman’s (1983) results regarding well-defined concepts such as ‘odd number’ illustrates the debate over typicality effects well. Their participants make conscious verbal report of whether a concept has a clear definition, and show the typical kinds of typicality effects that arise (gradient ratings, reaction times) even for well-defined concepts. Based on these results, the authors argue for graded typicality as a peripheral property rather than a constitutive aspect of a concept, whereas other researchers have argued these results show precisely the pervasiveness of gradient conceptual structure. Gleitman, Connolly, and Armstrong (2012) still argue that it is laughable to deny the clear-cut nature of arithmetic concepts.

Why should one, however, give privileged status to the participants’ conscious verbal report and the authors’ intuition regarding the ‘classical’ status of these concepts, while dismissing the typicality effects as merely incidental properties? After all, the problem goes back to how one defines a concept, but to those psychologists who don’t assume an absolute status of definitions external to our gradient mental representations, Armstrong and colleagues’ study reveals an assumption, rather than a demonstration, of classical concepts.

Osherson and Smith (1981; also Smith & Osherson, 1984) considered the feasibility of Zadeh’s (1965) fuzzy set theory and suggested that its limitations might generalize to all versions of prototype theory. After a brief mention of alternative versions of fuzzy logic and subsequent developments in the field, Osherson and Smith simply concluded that fuzzy logic is implausible because fuzzy truth is against our strong intuitions of truth. Again, this is no argument, but only an assumption. After all, I don’t think many people find quantum physics any more intuitive than Newtonian physics, but paradigm shifts occur regardless of our intuitions (and sometimes even reshape our intuitions – e.g., Copernican heliocentrism).

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A supplementary remark on a footnote in my forthcoming (but already submitted) dissertation:

The fact that there is no intuitive endpoint in the past – perhaps other than the Big Bang – does not mean there is no floor/asymptote to our epistemic modality regarding the past. The lack of an intuitive end to the infinitely projecting past doesn’t prevent an asymptote at 0% in subjective certainty, similar to the infinitely projecting future.

There does remain asymmetry in the structure of our subjective certainty about the past and the future, due to three factors that do not similarly complicate the future:

(1) autobiographical memory: Before this develops, everything would fall into the domain of evidentiality. A point near one’s birth (‘near’ here means ‘a few years after’) would thus be a major transition point for the epistemic modality of the past.

(2) history/records: At least we have written or oral records for periods of recorded history, but we can only theorize about “prehistoric” times. Fossils and experimental physics may help us a bit.

(3) The Big Bang: The precise impact of this on our folk knowledge of the past is unclear. (Many people may not even have heard of the Big Bang.)

In sum, the ‘unevenness’ of the “past modality” reveals itself in terms of sources of knowledge – being more restricted, first from a wide variety including one’s direct perception, to historians and archeologists, then to physicists (plus, there’s always one’s own speculation). The “future modality” isn’t uneven in the same manner, and it therefore isn’t exactly symmetric to the “past modality,” although both may be roughly monotonically decreasing with greater distances from the present.

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Humanities and science: Reflections after a workshop on NLP for literature

At a conference on human language technologies (NAACL-HLT 2012, Montreal), I participated in a stimulating discussion in the workshop on Computational Linguistics for Literature. The main issue we discussed was an ontological question about the field of NLP for literature – that is, whether such a field exists at all, and whether it is different from the digital humanities in any way.

Although researchers who are inherently interested in applying NLP to literary study can go ahead and do their research regardless of what the name of their field would be, the ontological questions do have impact on public perception of the field and of its utility, and thus policy and funding decisions as well. Policy and funding in turn have impact on instrumental motivation and practical considerations, which for some – if not most – researchers are difficult to tease apart from inherent motivation.

I expressed my opinion during the discussion that quantitative studies of literature are very promising and revealing interesting insights that complement more traditional approaches to literature. Of course, the NLP researchers working on literature are not attempting to provide all the answers to questions about literature; their answers are only a part of the picture, but a very important part. The empirical results they obtain on a large scale are simply impossible to obtain without automatic procedures. At the same time, these automated procedures for data coding or analysis should not be ‘dumb’ ones, but should rather be nuanced to reflect earlier insights in literary analysis, discourse analysis, sociolinguistics, and other relevant fields.

No one can claim a monopoly on research directions or methodologies, and neither qualitative nor quantitative methodology should be the only way to look at literature. A humanities scholar asked me whether I, as a cognitive scientist, would consider including the humanities in a cognitive science program/department. I would welcome it and embrace it (if I had any say in the matter), provided that the CogSci division of the humanities program offers something different (a scientific, quantitative approach) from a non-CogSci division employing traditional approaches – the two should co-exist, though not necessarily in the same department. I always enjoy and value interdisciplinary collaboration, and I was very glad to meet the like-minded scholars at the workshop. The trouble is, not everyone is so enlightened as a renaissance scholar. I can foresee a lot of sociological – this is a euphemism for ‘dogmatic’ – resistance to the idea of putting numbers on literature, even if it’s not intended as the only way of looking at literature.

Nevertheless, my kindred spirits and I will go on. Participating in the workshop led me to discover insightful and interesting work by Jerry Hobbs and Inderjeet Mani, among others, and also interact with up-and-coming scholars whom I hope I will continue to see at future workshops and conferences.

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Sometimes an idea is so beautiful that it shapes all your observations unawares.
Oftentimes the phenomenon can’t be denied, but have you got the right theory?

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Psycholinguistic insight in literature

“William coughed politely. ‘Er … hm …’ he said. This is what he did when he wanted to introduce a new subject. He managed to do it gracefully because it was his habit – and I believe this is typical of the men of his country – to begin every remark with long preliminary moans, as if starting the exposition of a completed thought cost him a great mental effort. Whereas, I am now convinced, the more groans he uttered before his declaration, the surer he was of the soundness of the proposition he was expressing.” (Umberto Eco, 1984, The name of the rose, p. 145)

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