Changing the culture of peer review for a more inclusive and equitable psychological science.

Peer review is a core component of scientific practice. Although peer review ideally improves research and promotes rigor, it also has consequences for what types of research are published and cited and who wants to (and is able to) advance in research-focused careers. Despite these consequences, few reviewers or editors receive training or oversight to ensure their feedback is helpful, professional, and culturally sensitive. Here, we critically examine the peer-review system in psychology and neuroscience at multiple levels, from ideas to institutions, interactions, and individuals. We highlight initiatives that aim to change the normative negativity of peer review and provide authors with constructive, actionable feedback that is sensitive to diverse identities, methods, topics, and environments. We conclude with a call to action for how individuals, groups, and organizations can improve the culture of peer review. We provide examples of how changes in the peer-review system can be made with an eye to diversity (increasing the range of identities and experiences constituting the field), equity (fair processes and outcomes across groups), and inclusion (experiences that promote belonging across groups). These changes can improve scientists' experience of peer review, promote diverse perspectives and identities, and enhance the quality and impact of science. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Reproducibility and a unifying explanation: Lessons from the shape bias.

The goal of science is to advance our understanding of particular phenomena. However, in the field of development, the phenomena of interest are complex, multifaceted, and change over time. Here, we use three decades of research on the shape bias to argue that while replication is clearly an important part of the scientific process, integration across the findings of many studies that include variations in procedure is also critical to create a coherent understanding of the thoughts and behaviors of young children. The "shape bias," or the tendency to generalize a novel label to novel objects of the same shape, is a reliable and robust behavioral finding and has been shown to predict future vocabulary growth and possible language disorders. Despite the robustness of the phenomenon, the way in which the shape bias is defined and tested has varied across studies and laboratories. The current review argues that differences in performance that come from even seemingly minor changes to the participants or task can offer critical insight to underlying mechanisms, and that working to incorporate data from multiple labs is an important way to reveal how task variation and a child's individual pathway creates behavior-a key issue for understanding developmental phenomena.

Not Only Size Matters: Early-Talker and Late-Talker Vocabularies Support Different Word-Learning Biases in Babies and Networks.

In typical development, word learning goes from slow and laborious to fast and seemingly effortless. Typically developing 2-year-olds seem to intuit the whole range of things in a category from hearing a single instance named-they have word-learning biases. This is not the case for children with relatively small vocabularies (late talkers). We present a computational model that accounts for the emergence of word-learning biases in children at both ends of the vocabulary spectrum based solely on vocabulary structure. The results of Experiment 1 show that late-talkers' and early-talkers' noun vocabularies have different structures and that neural networks trained on the vocabularies of individual late talkers acquire different word-learning biases than those trained on early-talker vocabularies. These models make novel predictions about the word-learning biases in these two populations. Experiment 2 tests these predictions on late- and early-talking toddlers in a novel noun generalization task.

Beyond modeling abstractions: learning nouns over developmental time in atypical populations and individuals.

Connectionist models that capture developmental change over time have much to offer in the field of language development research. Several models in the literature have made good contact with developmental data, effectively captured behavioral tasks, and accurately represented linguistic input available to young children. However, fewer models of language development have truly captured the process of developmental change over time. In this review paper, we discuss several prominent connectionist models of early word learning, focusing on semantic development, as well as our recent work modeling the emergence of word learning biases in different populations. We also discuss the potential of these kinds of models to capture children's language development at the individual level. We argue that a modeling approach that truly captures change over time has the potential to inform theory, guide research, and lead to innovations in early language intervention.

Bilingual and monolingual children attend to different cues when learning new words.

The way in which children learn language can vary depending on their language environment. Previous work suggests that bilingual children may be more sensitive to pragmatic cues from a speaker when learning new words than monolingual children are. On the other hand, monolingual children may rely more heavily on object properties than bilingual children do. In this study we manipulate these two sources of information within the same paradigm, using eye gaze as a pragmatic cue and similarity along different dimensions as an object cue. In the crucial condition, object and pragmatic cues were inconsistent with each other. Our results showed that in this ambiguous condition monolingual children attend more to object property cues whereas bilingual children attend more to pragmatic cues. Control conditions showed that monolingual children were sensitive to eye gaze and bilingual children were sensitive to similarity by shape; it was only when the cues were inconsistent that children's preference for one or the other cue was apparent. Our results suggest that children learn to weigh different cues depending on their relative informativeness in their environment.

Words can slow down category learning.

Words have been shown to influence many cognitive tasks, including category learning. Most demonstrations of these effects have focused on instances in which words facilitate performance. One possibility is that words augment representations, predicting an across the-board benefit of words during category learning. We propose that words shift attention to dimensions that have been historically predictive in similar contexts. Under this account, there should be cases in which words are detrimental to performance. The results from two experiments show that words impair learning of object categories under some conditions. Experiment 1 shows that words hurt performance when learning to categorize by texture. Experiment 2 shows that words also hurt when learning to categorize by brightness, leading to selectively attending to shape when both shape and hue could be used to correctly categorize stimuli. We suggest that both the positive and negative effects of words have developmental origins in the history of word usage while learning categories. [corrected]

Knowledge as process: contextually-cued attention and early word learning.

Learning depends on attention. The processes that cue attention in the moment dynamically integrate learned regularities and immediate contextual cues. This paper reviews the extensive literature on cued attention and attentional learning in the adult literature and proposes that these fundamental processes are likely significant mechanisms of change in cognitive development. The value of this idea is illustrated using phenomena in children novel word learning.

More than a matter of getting 'unstuck': flexible thinkers use more abstract representations than perseverators.

Why do people perseverate, repeating prior behaviours that are no longer appropriate? Many accounts point to isolated deficits in processes such as inhibition or attention. We instead posit a fundamental difference in rule representations: flexible switchers use active representations that rely on later-developing prefrontal cortical areas and are more abstract, whereas perseverators use latent representations that rely on earlier-developing posterior cortical and subcortical areas and are more stimulus-specific. Thus, although switchers and perseverators should apply the rules they use to familiar stimuli equally reliably, perseverators should show unique limitations in generalizing their rules to novel stimuli, a process that requires abstract representations. Two behavioural experiments confirmed this counterintuitive prediction early in development. Three-year-old children sorted cards by one rule, were asked to switch to another rule, and then were asked simply to continue their behaviour, with novel cards. Perseverators applied the rule they were using (the first rule) just as reliably as switchers applied the rule they were using (the second rule) with familiar cards; however, only switchers generalized their rule to novel cards. This finding supports an early link between active representations that support switching and abstract representations that support generalization. We interpret this synergy in terms of prefrontal cortical development.

Correlation versus prediction in children's word learning: Cross-linguistic evidence and simulations.

The ontological distinction between discrete individuated objects and continuous substances, and the way this distinction is expressed in different languages has been a fertile area for examining the relation between language and thought. In this paper we combine simulations and a cross-linguistic word learning task as a way to gain insight into the nature of the learning mechanisms involved in word learning. First, we look at the effect of the different correlational structures on novel generalizations with two kinds of learning tasks implemented in neural networks-prediction and correlation. Second, we look at English- and Spanish-speaking 2-3-year-olds' novel noun generalizations, and find that count/mass syntax has a stronger effect on Spanish- than on English-speaking children's novel noun generalizations, consistent with the predicting networks. The results suggest that it is not just the correlational structure of different linguistic cues that will determine how they are learned, but the specific learning mechanism and task in which they are involved.

Knowledge embedded in process: the self-organization of skilled noun learning.

Young children's skilled generalization of newly learned nouns to new instances has become the battleground for two very different approaches to cognition. This debate is a proxy for a larger dispute in cognitive science and cognitive development: cognition as rule-like amodal propositions, on the one hand, or as embodied, modal, and dynamic processes on the other. After a brief consideration of this theoretical backdrop, we turn to the specific task set before us: an overview of the Attentional Learning Account (ALA) of children's novel noun generalizations, the constrained set of experimental results to be explained, and our explanation of them. We conclude with a consideration of what all of this implies for a theory of cognitive development.

From the lexicon to expectations about kinds: a role for associative learning.

In the novel noun generalization task, 2 1/2-year-old children display generalized expectations about how solid and nonsolid things are named, extending names for never-before-encountered solids by shape and for never-before-encountered nonsolids by material. This distinction between solids and nonsolids has been interpreted in terms of an ontological distinction between objects and substances. Nine simulations and behavioral experiments tested the hypothesis that these expectations arise from the correlations characterizing early learned noun categories. In the simulation studies, connectionist networks were trained on noun vocabularies modeled after those of children. These networks formed generalized expectations about solids and nonsolids that match children's performances in the novel noun generalization task in the very different languages of English and Japanese. The simulations also generate new predictions supported by new experiments with children. Implications are discussed in terms of children's development of distinctions between kinds of categories and in terms of the nature of this knowledge.

The emergence of abstract ideas: evidence from networks and babies.

What is abstraction? In our view, abstraction is generalization. Specifically, we propose that abstract concepts emerge as the natural product of associative learning and generalization by similarity. We support this proposal by presenting evidence for two ideas: first, that children's knowledge about how categories are organized and how words refer to them can be explained as learned generalizations over specific experiences of words referring to categories; and second, that the path of concepts from concrete to more abstract can be observed throughout development and that even in their more abstract form, concepts retain some of their original sensory basis. We illustrate these two facts by examining, in two kinds of learners--networks and young children--the development of three abstract ideas: (i) the idea of word; (ii) the idea of object; and (iii) the idea of substance.

Whose DAM account? Attentional learning explains Booth and Waxman.

Booth and Waxman (Cognition 84 (2002) B11) have recently shown that linguistic cues to animacy affect children's novel name extensions. They argue that this demonstration contradicts two central tenets of our attentional learning account of object naming, which Booth and Waxman characterize as the "dumb attentional mechanism" or "DAM" account. In the present article, we show that the first of these tenets has never been a feature of the attentional learning account, and that the second tenet, which is central to our account, is not addressed by Booth and Waxman's findings. We suggest that the debate about the nature of children's language and cognition would profit from an increased awareness of the different levels of analysis at which different researchers are working.