Even laypeople use legalese.

Whereas principles of communicative efficiency and legal doctrine dictate that laws be comprehensible to the common world, empirical evidence suggests legal documents are largely incomprehensible to lawyers and laypeople alike. Here, a corpus analysis (n = 59) million words) first replicated and extended prior work revealing laws to contain strikingly higher rates of complex syntactic structures relative to six baseline genres of English. Next, two preregistered text generation experiments (n = 286) tested two leading hypotheses regarding how these complex structures enter into legal documents in the first place. In line with the magic spell hypothesis, we found people tasked with writing official laws wrote in a more convoluted manner than when tasked with writing unofficial legal texts of equivalent conceptual complexity. Contrary to the copy-and-edit hypothesis, we did not find evidence that people editing a legal document wrote in a more convoluted manner than when writing the same document from scratch. From a cognitive perspective, these results suggest law to be a rare exception to the general tendency in human language toward communicative efficiency. In particular, these findings indicate law's complexity to be derived from its performativity, whereby low-frequency structures may be inserted to signal law's authoritative, world-state-altering nature, at the cost of increased processing demands on readers. From a law and policy perspective, these results suggest that the tension between the ubiquity and impenetrability of the law is not an inherent one, and that laws can be simplified without a loss or distortion of communicative content.

Even lawyers do not like legalese.

Across modern civilization, societal norms and rules are established and communicated largely in the form of written laws. Despite their prevalence and importance, legal documents have long been widely acknowledged to be difficult to understand for those who are required to comply with them (i.e., everyone). Why? Across two preregistered experiments, we evaluated five hypotheses for why lawyers write in a complex manner. Experiment 1 revealed that lawyers, like laypeople, were less able to recall and comprehend legal content drafted in a complex "legalese" register than content of equivalent meaning drafted in a simplified register. Experiment 2 revealed that lawyers rated simplified contracts as equally enforceable as legalese contracts, and rated simplified contracts as preferable to legalese contracts on several dimensions-including overall quality, appropriateness of style, and likelihood of being signed by a client. These results suggest that lawyers who write in a convoluted manner do so as a matter of convenience and tradition as opposed to an outright preference and that simplifying legal documents would be both tractable and beneficial for lawyers and nonlawyers alike.

Diverse mathematical knowledge among indigenous Amazonians.

We investigate number and arithmetic learning among a Bolivian indigenous people, the Tsimane', for whom formal schooling is comparatively recent in history and variable in both extent and consistency. We first present a large-scale meta-analysis on child number development involving over 800 Tsimane' children. The results emphasize the impact of formal schooling: Children are only found to be full counters when they have attended school, suggesting the importance of cultural support for early mathematics. We then test especially remote Tsimane' communities and document the development of specialized arithmetical knowledge in the absence of direct formal education. Specifically, we describe individuals who succeed on arithmetic problems involving the number five-which has a distinct role in the local economy-even though they do not succeed on some lower numbers. Some of these participants can perform multiplication with fives at greater accuracy than addition by one. These results highlight the importance of cultural factors in early mathematics and suggest that psychological theories of number where quantities are derived from lower numbers via repeated addition (e.g., a successor function) are unlikely to explain the diversity of human mathematical ability.

Distributed Sensitivity to Syntax and Semantics throughout the Language Network.

Human language is expressive because it is compositional: The meaning of a sentence (semantics) can be inferred from its structure (syntax). It is commonly believed that language syntax and semantics are processed by distinct brain regions. Here, we revisit this claim using precision fMRI methods to capture separation or overlap of function in the brains of individual participants. Contrary to prior claims, we find distributed sensitivity to both syntax and semantics throughout a broad frontotemporal brain network. Our results join a growing body of evidence for an integrated network for language in the human brain within which internal specialization is primarily a matter of degree rather than kind, in contrast with influential proposals that advocate distinct specialization of different brain areas for different types of linguistic functions.

The forms and meanings of grammatical markers support efficient communication.

Functionalist accounts of language suggest that forms are paired with meanings in ways that support efficient communication. Previous work on grammatical marking suggests that word forms have lengths that enable efficient production, and work on the semantic typology of the lexicon suggests that word meanings represent efficient partitions of semantic space. Here we establish a theoretical link between these two lines of work and present an information-theoretic analysis that captures how communicative pressures influence both form and meaning. We apply our approach to the grammatical features of number, tense, and evidentiality and show that the approach explains both which systems of feature values are attested across languages and the relative lengths of the forms for those feature values. Our approach shows that general information-theoretic principles can capture variation in both form and meaning across languages.

So much for plain language: An analysis of the accessibility of U.S. federal laws over time.

Over the last 50 years, there have been efforts on behalf of the U.S. government to simplify legal documents for society at large. However, there has been no systematic evaluation of how effective these efforts-collectively referred to as the "plain-language movement"-have been. Here we report the results of a large-scale longitudinal corpus analysis (n ≈ 225 million words), in which we compared every law passed by congress with a comparably sized sample of English texts from four different baseline genres published during approximately the same time period. We also compared the entirety of the U.S. Code (the official compilation of all federal legislation currently in force) with a large sample of recently published texts from six baseline genres of English. We found that laws remain laden with features associated with psycholinguistic complexity-including center-embedding, passive voice, low-frequency jargon, capitalization, and sentence length-relative to the baseline genres of English, and that the prevalence of most of these features has not meaningfully declined since the initial onset of the plain-language efforts. These findings suggest top-down efforts to simplify legal texts have thus far remained largely ineffectual, despite the apparent tractability of these changes, and call into question the coherence and legitimacy of legal doctrines whose validity rests on the notion of laws being easily interpretable by laypeople. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Logical word learning: The case of kinship.

We examine the conceptual development of kinship through the lens of program induction. We present a computational model for the acquisition of kinship term concepts, resulting in the first computational model of kinship learning that is closely tied to developmental phenomena. We demonstrate that our model can learn several kinship systems of varying complexity using cross-linguistic data from English, Pukapuka, Turkish, and Yanomamö. More importantly, the behavioral patterns observed in children learning kinship terms, under-extension and over-generalization, fall out naturally from our learning model. We then conducted interviews to simulate realistic learning environments and demonstrate that the characteristic-to-defining shift is a consequence of our learning model in naturalistic contexts containing abstract and concrete features. We use model simulations to understand the influence of logical simplicity and children's learning environment on the order of acquisition of kinship terms, providing novel predictions for the learning trajectories of these words. We conclude with a discussion of how this model framework generalizes beyond kinship terms, as well as a discussion of its limitations.

Poor writing, not specialized concepts, drives processing difficulty in legal language.

Despite their ever-increasing presence in everyday life, contracts remain notoriously inaccessible to laypeople. Why? Here, a corpus analysis (n ≈10 million words) revealed that contracts contain startlingly high proportions of certain difficult-to-process features-including low-frequency jargon, center-embedded clauses (leading to long-distance syntactic dependencies), passive voice structures, and non-standard capitalization-relative to nine other baseline genres of written and spoken English. Two experiments (N=184) further revealed that excerpts containing these features were recalled and comprehended at lower rates than excerpts without these features, even for experienced readers, and that center-embedded clauses inhibited recall more-so than other features. These findings (a) undermine the specialized concepts account of legal theory, according to which law is a system built upon expert knowledge of technical concepts; (b) suggest such processing difficulties result largely from working-memory limitations imposed by long-distance syntactic dependencies (i.e., poor writing) as opposed to a mere lack of specialized legal knowledge; and (c) suggest editing out problematic features of legal texts would be tractable and beneficial for society at-large.

Speakers and listeners exploit word order for communicative efficiency: A cross-linguistic investigation.

Pragmatic theories and computational models of reference must account for people's frequent use of redundant color adjectives (e.g., referring to a single triangle as "the blue triangle"). The standard pragmatic view holds that the informativity of a referential expression depends on pragmatic contrast: Color adjectives should be used to contrast competitors of the same kind to preempt an ambiguity (e.g., between several triangles of different colors), otherwise they are redundant. Here we propose an alternative to the standard view, the incremental efficiency hypothesis, according to which the efficiency of a referential expression must be calculated incrementally over the entire visual context. This is the first theoretical account of referential efficiency that is sensitive to the incrementality of language processing, making different cross-linguistic predictions depending on word order. Experiment 1 confirmed that English speakers produced more redundant color adjectives (e.g., "the blue triangle") than Spanish speakers (e.g., "el triángulo azul"), but both language groups used more redundant color adjectives in denser displays where it would be more efficient. In Experiments 2A and 2B, we used eye tracking to show that pragmatic contrast is not a processing constraint. Instead, incrementality and efficiency determine that English listeners establish color contrast across categories (BLUE SHAPES > TRIANGULAR ONE), whereas Spanish listeners establish color contrast within a category (TRIANGLES > BLUE ONE). Spanish listeners, however, reversed their visual search strategy when tested in English immediately after. Our results show that speakers and listeners of different languages exploit word order to increase communicative efficiency. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Contrast perception as a visual heuristic in the formulation of referential expressions.

We hypothesize that contrast perception works as a visual heuristic, such that when speakers perceive a significant degree of contrast in a visual context, they tend to produce the corresponding adjective to describe a referent. The contrast perception heuristic supports efficient audience design, allowing speakers to produce referential expressions with minimum expenditure of cognitive resources, while facilitating the listener's visual search for the referent. We tested the perceptual contrast hypothesis in three language-production experiments. Experiment 1 revealed that speakers overspecify color adjectives in polychrome displays, whereas in monochrome displays they overspecified other properties that were contrastive. Further support for the contrast perception hypothesis comes from a re-analysis of previous work, which confirmed that color contrast elicits color overspecification when detected in a given display, but not when detected across monochrome trials. Experiment 2 revealed that even atypical colors (which are often overspecified) are only mentioned if there is color contrast. In Experiment 3, participants named a target color faster in monochrome than in polychrome displays, suggesting that the effect of color contrast is not analogous to ease of production. We conclude that the tendency to overspecify color in polychrome displays is not a bottom-up effect driven by the visual salience of color as a property, but possibly a learned communicative strategy. We discuss the implications of our account for pragmatic theories of referential communication and models of audience design, challenging the view that overspecification is a form of egocentric behavior.

Composition is the Core Driver of the Language-selective Network.

The frontotemporal language network responds robustly and selectively to sentences. But the features of linguistic input that drive this response and the computations that these language areas support remain debated. Two key features of sentences are typically confounded in natural linguistic input: words in sentences (a) are semantically and syntactically combinable into phrase- and clause-level meanings, and (b) occur in an order licensed by the language's grammar. Inspired by recent psycholinguistic work establishing that language processing is robust to word order violations, we hypothesized that the core linguistic computation is composition, and, thus, can take place even when the word order violates the grammatical constraints of the language. This hypothesis predicts that a linguistic string should elicit a sentence-level response in the language network provided that the words in that string can enter into dependency relationships as in typical sentences. We tested this prediction across two fMRI experiments (total N = 47) by introducing a varying number of local word swaps into naturalistic sentences, leading to progressively less syntactically well-formed strings. Critically, local dependency relationships were preserved because combinable words remained close to each other. As predicted, word order degradation did not decrease the magnitude of the blood oxygen level-dependent response in the language network, except when combinable words were so far apart that composition among nearby words was highly unlikely. This finding demonstrates that composition is robust to word order violations, and that the language regions respond as strongly as they do to naturalistic linguistic input, providing that composition can take place.

Humans store about 1.5 megabytes of information during language acquisition.

We introduce theory-neutral estimates of the amount of information learners possess about how language works. We provide estimates at several levels of linguistic analysis: phonemes, wordforms, lexical semantics, word frequency and syntax. Our best guess is that the average English-speaking adult has learned 12.5 million bits of information, the majority of which is lexical semantics. Interestingly, very little of this information is syntactic, even in our upper bound analyses. Generally, our results suggest that learners possess remarkable inferential mechanisms capable of extracting, on average, nearly 2000 bits of information about how language works each day for 18 years.

How do you know that? Automatic belief inferences in passing conversation.

There is an ongoing debate, both in philosophy and psychology, as to whether people are able to automatically infer what others may know, or whether they can only derive belief inferences by deploying cognitive resources. Evidence from laboratory tasks, often involving false beliefs or visual-perspective taking, has suggested that belief inferences are cognitively costly, controlled processes. Here we suggest that in everyday conversation, belief reasoning is pervasive and therefore potentially automatic in some cases. To test this hypothesis, we conducted two pre-registered self-paced reading experiments (N1 = 91, N2 = 89). The results of these experiments showed that participants slowed down when a stranger commented 'That greasy food is bad for your ulcer' relative to conditions where a stranger commented on their own ulcer or a friend made either comment - none of which violated participants' common-ground expectations. We conclude that Theory of Mind models need to account for belief reasoning in conversation as it is at the center of everyday social interaction.