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Pseudonyms as carriers of contextualised threat in 19th-century Irish English threatening notices
(2021)
This paper explores functions of pseudonyms in written threatening communication from a cognitive sociolinguistic perspective. It addresses the semantic domains present in pseudonyms in a corpus of 19th-century Irish English threatening notices and their cognitive functions in the construction of both cultural-contextualised threat and the threatener's identity. We identify eight semantic domains that are accessed recurrently in order to create threat. Contributing to the notion of threat involves menacing war, violence, darkness and perdition directly, while also constructing a certain persona for the threatener that highlights their motivation, moral superiority, historical, local and circumstantial expertise, and their physical and mental aptitude. We argue that pseudonyms contribute to the deontic force of the threat by accessing cultural categories and schemas as well as conceptual metaphors and metonymies. Finally, we suggest that pseudonyms function as post-positioned semantic frame setters, providing a cognitive lens through which the entire threatening notice must be interpreted.
During reading or listening, people can generate predictions about the lexical and morphosyntactic properties of upcoming input based on available context. Psycholinguistic experiments that study predictability or control for it conventionally rely on a human-based approach and estimate predictability via the cloze task. Our study investigated an alternative corpus-based approach for estimating predictability via language predictability models. We obtained cloze and corpus-based probabilities for all words in 144 Russian sentences, correlated the two measures, and found a strong correlation between them. Importantly, we estimated how much variance in eye movements registered while reading the same sentences was explained by each of the two probabilities and whether the two probabilities explain the same variance. Along with lexical predictability (the activation of a particular word form), we analyzed morphosyntactic predictability (the activation of morphological features of words) and its effect on reading times over and above lexical predictability. We found that for predicting reading times, cloze and corpus-based measures of both lexical and morphosyntactic predictability explained the same amount of variance. However, cloze and corpus-based lexical probabilities both independently contributed to a better model fit, whereas for morphosyntactic probabilities, the contributions of cloze and corpus-based measures were interchangeable. Therefore, morphosyntactic but not lexical corpus-based probabilities can substitute for cloze probabilities in reading experiments. Our results also indicate that in languages with rich inflectional morphology, such as Russian, when people engage in prediction, they are much more successful in predicting isolated morphosyntactic features than predicting the particular lexeme and its full morphosyntactic markup.
In successful communication, the literal meaning of linguistic utterances is often enriched by pragmatic inferences. Part of the pragmatic reasoning underlying such inferences has been successfully modeled as Bayesian goal recognition in the Rational Speech Act (RSA) framework. In this paper, we try to model the interpretation of question-answer sequences with narrow focus in the answer in the RSA framework, thereby exploring the effects of domain size and prior probabilities on interpretation. Should narrow focus exhaustivity inferences be actually based on Bayesian inference involving prior probabilities of states, RSA models should predict a dependency of exhaustivity on these factors. We present experimental data that suggest that interlocutors do not act according to the predictions of the RSA model and that exhaustivity is in fact approximately constant across different domain sizes and priors. The results constitute a conceptual challenge for Bayesian accounts of the underlying pragmatic inferences.
Substantial research has examined cognition in aging bilinguals. However, less work has investigated the effects of aging on language itself in bilingualism. In this article I comprehensively review prior research on this topic, and interpret the evidence in light of current theories of aging and theories of bilingualism. First, aging indeed appears to affect bilinguals' language performance, though there is considerable variability in the trajectory across adulthood (declines, age-invariance, and improvements) and in the extent to which these trajectories resemble those found in monolinguals. I argue that these age effects are likely explained by the key opposing forces of increasing experience and cognitive declines in aging. Second, consistent with some theoretical work on bilingual language processing, the grammatical processing mechanisms do not seem to change between younger and older bilingual adults, even after decades of immersion. I conclude by discussing how future research can further advance the field.
How to embrace variation and accept uncertainty in linguistic and psycholinguistic data analysis
(2021)
The use of statistical inference in linguistics and related areas like psychology typically involves a binary decision: either reject or accept some null hypothesis using statistical significance testing. When statistical power is low, this frequentist data-analytic approach breaks down: null results are uninformative, and effect size estimates associated with significant results are overestimated. Using an example from psycholinguistics, several alternative approaches are demonstrated for reporting inconsistencies between the data and a theoretical prediction. The key here is to focus on committing to a falsifiable prediction, on quantifying uncertainty statistically, and learning to accept the fact that - in almost all practical data analysis situations - we can only draw uncertain conclusions from data, regardless of whether we manage to obtain statistical significance or not. A focus on uncertainty quantification is likely to lead to fewer excessively bold claims that, on closer investigation, may turn out to be not supported by the data.
The interpretation of negated antonyms is characterised by a polarity asymmetry: the negation of a positive polarity antonym (X is not interesting) is more likely to be strengthened to convey its opposite ('X is uninteresting') than the negation of a negative polarity antonym (X is not uninteresting to convey that 'X is interesting') is. A classical explanation of this asymmetry relies on face-management. Since the predication of a negative polarity antonym (X is uninteresting) is potentially face-threatening in most contexts, the negation of the corresponding positive polarity antonym (X is not interesting) is more likely to be interpreted as an indirect strategy to minimise face-threat while getting the message across. We present two experimental studies in which we test the predictions of this explanation. In contrast with it, our results show that adjectival polarity, but not face-threatening potential, appears to be responsible for the asymmetric interpretation of negated antonyms.
Comparisons of equality with German so ... wie, and the relationship between degrees and properties
(2021)
We present a compositionally transparent, unified semantic analysis of two kinds of so ... wie-equative constructions in German, namely degree equatives and property equatives in the domain of individuals or events. Unlike in English and many other European languages (Haspelmath & Buchholz 1998, Rett 2013), both equative types in German feature the parameter marker so, suggesting a unified analysis. We show that the parallel formal expression of German degree and property equatives is accompanied by a parallel syntactic distribution (in predicative, attributive, and adverbial position), and by identical semantic properties: Both equative types allow for scope ambiguities, show negative island effects out of context, and license the negative polarity item uberhaupt 'at all' in the complement clause. As the same properties are also shared by German comparatives, we adopt the influential quantificational analysis of comparatives in von Stechow (1984ab), Heim (1985, 2001, 2007), and Beck (2011), and treat both German equative types in a uniform manner as expressing universal quantification over sets of degrees or over sets of properties (of individuals or events). Conceptually, the uniform marking of degree-related and property-related meanings is expected given that the abstract semantic category degree (type ) can be reconstructed in terms of equivalence classes, i.e., ontologically simpler sets of individuals (type ) or events (type ). These are found in any language, showing that whether or not a language makes explicit reference to degrees (by means of gradable adjectives, degree question words, degree-only equatives) does not follow on general conceptual or semantic grounds, but is determined by the grammar of that language.
We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better accounted for by an encoding-based model of agreement attraction, compared to a retrieval-based model. A novel methodological contribution of our study is the use of comprehension questions with open-ended responses, so that both misinterpretation of the number feature of the subject phrase and misassignment of the thematic subject role of the verb can be investigated at the same time. We find evidence for both types of misinterpretation in our study, sometimes in the same trial. However, the specific error patterns in our data are not fully consistent with any previously proposed model.
Apples and oranges
(2021)
Despite scarce empirical evidence, introducing new vocabulary in semantic categories has long been standard in second language teaching. We examined the effect of learning context on encoding, immediate recall and integration of new vocabulary into semantic memory by contrasting categorically related (novel names for familiar concepts blocked by semantic category) and unrelated (mixed semantic categories) learning contexts. Two learning sessions were conducted 24 hours apart, with each participant exposed to both contexts. Subsequently, a test phase examined picture naming, translation and picture-word interference tasks. Compared to the unrelated context, the categorically related context resulted in poorer naming accuracy in the learning phase, slower response latencies at the immediate recall tasks and greater semantic interference in the picture-word interference task (picture naming in L1 with semantically related novel word distractors). We develop a theoretical account of word learning that attributes observed differences to episodic rather than semantic memory.
Preregistration is an open science practice that requires the specification of research hypotheses and analysis plans before the data are inspected. Here, we discuss the benefits of preregistration for hypothesis-driven, confirmatory bilingualism research. Using examples from psycholinguistics and bilingualism, we illustrate how non-peer reviewed preregistrations can serve to implement a clean distinction between hypothesis testing and data exploration. This distinction helps researchers avoid casting post-hoc hypotheses and analyses as confirmatory ones. We argue that, in keeping with current best practices in the experimental sciences, preregistration, along with sharing data and code, should be an integral part of hypothesis-driven bilingualism research.