Archive for Bibliography

Bibliographical cornucopia for linguists, part 1

Bibliographical cornucopia for linguists, part 1

Since we have such an abundance of interesting articles for this fortnight, I will divide the collection into two parts, and provide each entry with an abstract or paragraph length quotation.

A fundamental question in word learning is how, given only evidence about what objects a word has previously referred to, children are able to generalize to the correct class. How does a learner end up knowing that “poodle” only picks out a specific subset of dogs rather than the broader class and vice versa? Numerous phenomena have been identified in guiding learner behavior such as the “suspicious coincidence effect” (SCE)—that an increase in the sample size of training objects facilitates more narrow (subordinate) word meanings. While SCE seems to support a class of models based in statistical inference, such rational behavior is, in fact, consistent with a range of algorithmic processes. Notably, the broadness of semantic generalizations is further affected by the temporal manner in which objects are presented—either simultaneously or sequentially. First, I evaluate the experimental evidence on the factors influencing generalization in word learning. A reanalysis of existing data demonstrates that both the number of training objects and their presentation-timing independently affect learning. This independent effect has been obscured by prior literature’s focus on possible interactions between the two. Second, I present a computational model for learning that accounts for both sets of phenomena in a unified way. The Naïve Generalization Model (NGM) offers an explanation of word learning phenomena grounded in category formation. Under the NGM, learning is local and incremental, without the need to perform a global optimization over pre-specified hypotheses. This computational model is tested against human behavior on seven different experimental conditions for word learning, varying over presentation-timing, number, and hierarchical relation between training items. Looking both at qualitative parameter-independent behavior and quantitative parameter-tuned output, these results support the NGM and suggest that rational learning behavior may arise from local, mechanistic processes rather than global statistical inference.

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Library lists

[Posted with the permission of the author, David Helliwell]
 
Almost exactly five years ago, I was dismissed on the grounds of age from my post as Curator of Chinese Collections at the Bodleian Library. I had been in office for over 41 years. The last six of those were particularly pleasurable as I was able to spend all my time organising, identifying, and cataloguing the Library’s “special collections” of Chinese books. Meanwhile, Joshua, who had been appointed to take over all my other duties, did all the hard work.

My teenage years were spent in the 1960s, and we children of the sixties, as demonstrated so well by Paul McCartney at Glastonbury this year, never grow old. We simply become less young. We also have the advantage of being able to recall what to many, if not to most colleagues in this room, is the distant past.

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Brain Mechanisms and Constructed Languages vs. Natural Languages

"Constructed Languages Are Processed by the Same Brain Mechanisms as Natural Languages." Malik-Moraleda, Saima, et al. Proceedings of the National Academy of Sciences 122, no. 12 (March 17, 2025): e2313473122.

Significance

What constitutes a language has been of interest to diverse disciplines—from philosophy and linguistics to psychology, anthropology, and sociology. An empirical approach is to test whether the system in question recruits the brain system that processes natural languages. Despite their similarity to natural languages, math and programming languages recruit a distinct brain system. Using fMRI, we test brain responses to constructed languages (conlangs)—which share features with both natural languages and programming languages—and find that they are processed by the same brain network as natural languages. Thus, an ability for a symbolic system to express diverse meanings about the world—but not the recency, manner, and purpose of its creation, or a large user base—is a defining characteristic of a language.

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Words for "library" in Sanskrit: the future of information science

The words that leap to mind are pustakālaya पुस्तकालय (pustak पुस्तक ["book"] + ālaya आलय ["place"]) and granthālaya ग्रन्थालय (granth ग्रंथ ["text"] + ālaya आलय ["place"]).  Those are simple and straightforward.

There were several other Sanskrit words for library I used to know, such as vidyākośasamāśraya विद्याकोशसमाश्रय* that included the component vidya ("knowledge"), but they were more subtle and complicated, so they were harder for me to recall.

*knowledge treasury coming together (for support or shelter)

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Linguistics bibliography roundup

Something for everyone

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