MétaCan
Menu
Back to cohort
Record W2018405720 · doi:10.1353/lan.2001.0100

<b>Syntactic nuts:</b> Hard cases, syntactic theory, and language acquisition. By Peter W. Culicover Oxford: Oxford University Press, 1999. Pp. viii, 244. Paper £16.99.

2001· article· en· W2018405720 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLanguage · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicLanguage and cultural evolution
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsUniversal grammarLinguistic universalGenerative grammarSyntaxLanguage acquisitionComputer scienceSecond-language acquisitionTheoretical linguisticsGrammarPhilosophy

Abstract

fetched live from OpenAlex

Reviewed by: Syntactic nuts: Hard cases, syntactic theory, and language acquisition by Peter W. Culicover Asya Pereltsvaig Syntactic nuts: Hard cases, syntactic theory, and language acquisition. By Peter W. Culicover. Oxford: Oxford University Press, 1999. Pp. viii, 244. Paper £16.99. This book sheds new light on the place of linguistic theory within cognitive science by investigating the architecture of the language faculty. In particular, it [End Page 404] explores what the properties of language reveal about the mental abilities and processes involved in language acquisition. The originality of this book is that it goes against the prevailing trend in generative grammar by considering not only what is general, exceptionless, and universal in language but also what is irregular, exceptional, and idiosyncratic, both in the lexicon and in syntax. In the first chapter, Culicover discusses the relationship between the study of the learning mechanism for language and the investigation of the properties of language itself as bounding conditions on such a mechanism. He argues that in addition to accounting for linguistic universals, linguistic theory should be able to accept that natural languages are ‘more than simply realizations of combinations of fixed sets of universal properties’ (1). Thus, he focuses on the acquisition of properties that a particular language does not share with other languages. Another question brought up in the first chapter is that of biology vs. learning, namely of how much of linguistic knowledge is biologically determined and how much is learned. Going against the general position, C argues that this question is an empirical one rather than a matter of dogma or ideology. In the last section of the introductory chapter, C identifies two important global properties that a language learner must have: conservatism, which precludes him from generalizing significantly beyond the evidence that is presented to him, and attentiveness, which makes him form generalizations based on all and only the evidence presented to him. The rest of the book is organized into three chapters that deal with categories, constructions, and constraints, respectively. The first of these chapters presents empirical evidence to support the claim that there is in principle an unbounded set of syntactic categories in natural language. C investigates elements that seem to belong to more than one traditional syntactic category, including either, the prepositional complementizer for, various determiners and quantifiers, and odd prepositions. He argues that such elements form separate categories. On the other hand, their apparent patterning with one or the other of the traditional syntactic categories may be explained from their conceptual structure properties rather than syntactic categorization. In Ch. 3, C considers a range of syntactic constructions that possess a certain degree of idiosyncrasy, including reduction constructions (e.g. sluicing), movement constructions (e.g. partial wh-movement), and inflections (e.g. do-support). He argues that even though these constructions might normally be taken as part of ‘core’ grammar, some of these aspects cannot be derived from universal principles and therefore must be determined by the learner on the basis of positive experience. In Ch. 4, C explores some of the consequences of taking the learner to be a conservative attentive learner. He applies the Hawkins Metric to develop a preliminary account of which generalizations are more accessible to the learner on the basis of positive evidence. The goal of this chapter is to provide an understanding of how a learner can acquire constructions that appear to be exceptions to ‘universal’ constraints. Even though the book is mainly concerned with English, other languages, such as Italian, Icelandic, Hungarian, and French, are discussed as well. Asya Pereltsvaig McGill University Copyright © 2001 Linguistic Society of America

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.244
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it