United States-China differences in cognition and perception across 12 tasks: Replicability, robustness, and within-culture variation.

Cultural differences between the United States and China have been investigated using a broad array of psychological tasks measuring differences between cognition, language, perception, and reasoning. Using online convenience samples of adults, we conducted two large-scale replications of 12 tasks previously reported to show differences between Western and East Asian cultures. Our results showed a heterogeneous pattern of successes and failures: five tasks yielded robust cultural differences, while five showed no difference between cultures, and two showed a small difference in the opposite direction. We observed moderate reliability for all multitrial tasks, but there was little relation between task scores. As in prior work, cross-cultural differences in cognition (in those tasks showing differences) were not strongly related to explicit measures of cultural identity and behavior. All of our tasks, data, and analyses are openly available for reuse, providing a foundation for future studies that seek to establish a robust and replicable science of cross-cultural difference. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A unified approach to demographic data collection for research with young children across diverse cultures.

Culture is a key determinant of children's development both in its own right and as a measure of generalizability of developmental phenomena. Studying the role of culture in development requires information about participants' demographic backgrounds. However, both reporting and treatment of demographic data are limited and inconsistent in child development research. A barrier to reporting demographic data in a consistent fashion is that no standardized tool currently exists to collect these data. Variation in cultural expectations, family structures, and life circumstances across communities make the creation of a unifying instrument challenging. Here, we present a framework to standardize demographic reporting for early child development (birth to 3 years of age), focusing on six core sociodemographic construct categories: biological information, gestational status, health status, community of descent, caregiving environment, and socioeconomic status. For each category, we discuss potential constructs and measurement items and provide guidance for their use and adaptation to diverse contexts. These items are stored in an open repository of context-adapted questionnaires that provide a consistent approach to obtaining and reporting demographic information so that these data can be archived and shared in a more standardized format. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Relational reasoning and generalization using nonsymbolic neural networks.

The notion of equality (identity) is simple and ubiquitous, making it a key case study for broader questions about the representations supporting abstract relational reasoning. Previous work suggested that neural networks were not suitable models of human relational reasoning because they could not represent mathematically identity, the most basic form of equality. We revisit this question. In our experiments, we assess out-of-sample generalization of equality using both arbitrary representations and representations that have been pretrained on separate tasks to imbue them with structure. We find neural networks are able to learn (a) basic equality (mathematical identity), (b) sequential equality problems (learning ABA-patterned sequences) with only positive training instances, and (c) a complex, hierarchical equality problem with only basic equality training instances ("zero-shot" generalization). In the two latter cases, our models perform tasks proposed in previous work to demarcate human-unique symbolic abilities. These results suggest that essential aspects of symbolic reasoning can emerge from data-driven, nonsymbolic learning processes. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Peekbank: An open, large-scale repository for developmental eye-tracking data of children's word recognition.

The ability to rapidly recognize words and link them to referents is central to children's early language development. This ability, often called word recognition in the developmental literature, is typically studied in the looking-while-listening paradigm, which measures infants' fixation on a target object (vs. a distractor) after hearing a target label. We present a large-scale, open database of infant and toddler eye-tracking data from looking-while-listening tasks. The goal of this effort is to address theoretical and methodological challenges in measuring vocabulary development. We first present how we created the database, its features and structure, and associated tools for processing and accessing infant eye-tracking datasets. Using these tools, we then work through two illustrative examples to show how researchers can use Peekbank to interrogate theoretical and methodological questions about children's developing word recognition ability.

Different reference frames on different axes: Space and language in indigenous Amazonians.

Spatial cognition is central to human behavior, but the way people conceptualize space varies within and across groups for unknown reasons. Here, we found that adults from an indigenous Bolivian group used systematically different spatial reference frames on different axes, according to known differences in their discriminability: In both verbal and nonverbal tests, participants preferred allocentric (i.e., environment-based) space on the left-right axis, where spatial discriminations (like "b" versus "d") are notoriously difficult, but the same participants preferred egocentric (i.e., body-based) space on the front-back axis, where spatial discrimination is relatively easy. The results (i) establish a relationship between spontaneous spatial language and memory across axes within a single culture, (ii) challenge the claim that each language group has a predominant spatial reference frame at a given scale, and (iii) suggest that spatial thinking and language may both be shaped by spatial discrimination abilities, as they vary across cultures and contexts.

Context shapes early diversity in abstract thought.

Early abstract reasoning has typically been characterized by a "relational shift," in which children initially focus on object features but increasingly come to interpret similarity in terms of structured relations. An alternative possibility is that this shift reflects a learned bias, rather than a typical waypoint along a universal developmental trajectory. If so, consistent differences in the focus on objects or relations in a child's learning environment could create distinct patterns of relational reasoning, influencing the type of hypotheses that are privileged and applied. Specifically, children in the United States may be subject to culture-specific influences that bias their reasoning toward objects, to the detriment of relations. In experiment 1, we examine relational reasoning in a population with less object-centric experience-3-y-olds in China-and find no evidence of the failures observed in the United States at the same age. A second experiment with younger and older toddlers in China (18 to 30 mo and 30 to 36 mo) establishes distinct developmental trajectories of relational reasoning across the two cultures, showing a linear trajectory in China, in contrast to the U-shaped trajectory that has been previously reported in the United States. In a third experiment, Chinese 3-y-olds exhibit a bias toward relational solutions in an ambiguous context, while those in the United States prefer object-based solutions. Together, these findings establish population-level differences in relational bias that predict the developmental trajectory of relational reasoning, challenging the generality of an initial object focus and suggesting a critical role for experience.

Languages Support Efficient Communication about the Environment: Words for Snow Revisited.

The claim that Eskimo languages have words for different types of snow is well-known among the public, but has been greatly exaggerated through popularization and is therefore viewed with skepticism by many scholars of language. Despite the prominence of this claim, to our knowledge the line of reasoning behind it has not been tested broadly across languages. Here, we note that this reasoning is a special case of the more general view that language is shaped by the need for efficient communication, and we empirically test a variant of it against multiple sources of data, including library reference works, Twitter, and large digital collections of linguistic and meteorological data. Consistent with the hypothesis of efficient communication, we find that languages that use the same linguistic form for snow and ice tend to be spoken in warmer climates, and that this association appears to be mediated by lower communicative need to talk about snow and ice. Our results confirm that variation in semantic categories across languages may be traceable in part to local communicative needs. They suggest moreover that despite its awkward history, the topic of "words for snow" may play a useful role as an accessible instance of the principle that language supports efficient communication.