As a reflection of prominent cultural norms, children’s literature plays an integral role in the acquisition and development of societal attitudes. Previous reports of male overrepresentation in books targeted towards children are consistent with a history of gender disparity across media and society. However, it is unknown whether such bias has been attenuated in recent years with increasing emphasis on gender equity and greater accessibility of books. Here, we provide an up-to-date estimate of the relative proportion of males and females featured as single protagonists in 3,280 children’s books (0–16 years) published between 1960–2020. We find that although the proportion of female protagonists has increased over this 60-year period, male protagonists remain overrepresented even in recent years. Importantly, we also find persistent effects related to author gender, age of the target audience, character type (human vs. non-human), and book genre (fiction vs. non-fiction) on the male-to-female ratio of protagonists. We suggest that this comprehensive account of the factors influencing the rates of appearance of male and female protagonists can be leveraged to develop specific recommendations for promoting more equitable gender representation in children’s literature, with important consequences for child development and society.

Understanding the trends and predictors of attrition rate, or the proportion of collected data that is excluded from the final analyses, is important for accurate research planning, assessing data integrity, and ensuring generalizability. In this pre‐registered meta‐analysis, we reviewed 182 publications in infant (0–24 months) functional near‐infrared spectroscopy (fNIRS) research published from 1998 to April 9, 2020, and investigated the trends and predictors of attrition. The average attrition rate was 34.23% among 272 experiments across all 182 publications. Among a subset of 136 experiments that reported the specific reasons for subject exclusion, 21.50% of the attrition was infant‐driven, while 14.21% was signal‐driven. Subject characteristics (e.g., age) and study design (e.g., fNIRS cap configuration, block/trial design, and stimulus type) predicted the total and subject‐driven attrition rates, suggesting that modifying the recruitment pool or the study design can meaningfully reduce the attrition rate in infant fNIRS research. Based on the findings, we established guidelines for reporting the attrition rate for scientific transparency and made recommendations to minimize the attrition rates. This research can facilitate developmental cognitive neuroscientists in their quest toward increasingly rigorous and representative research.

Why do infants learn some words earlier than others? To explain how and when words are learned, existing theories of word learning prioritize visual information and draw mainly on lab-based studies of noun-to-object mapping. However, words that are more abstract than object nouns, such as uh-oh, hi, more, up, and all-gone, are typically among the first to appear in infants' vocabularies. We combined a behavioral experiment with naturalistic observational research to explore how infants learn and represent this understudied category of high-frequency, routine-based non-nouns, which we term ‘everyday words’. In Study 1, we found that conventional eye-tracking measures of comprehension were insufficient to capture 10- to 16-month-old infants' emerging understanding of everyday words. In Study 2, we analyzed the visual and social scenes surrounding caregivers' and infants' use of everyday words in a naturalistic video corpus. This ecologically-motivated research revealed that everyday words rarely co-occurred with consistent visual referents, making their early learnability difficult to reconcile with dominant word learning theories. Our findings instead point to complex patterns in the types of situations associated with everyday words that could contribute to their early representation in infants’ vocabularies. By leveraging both experimental and observational methods, this investigation underscores the value of using naturalistic data to broaden theories of early learning.

Object-centric interactions provide rich learning moments for young children, including opportunities to discover word meanings. Children’s first-person object handling experiences, in particular, form a key source of input—one that varies across cultures and across development. Using daylong photo streams from child-worn cameras, we analyze >17k images to identify the frequency and targets of child object handling across the first four years in two small-scale subsistence farming communities on opposite sides of the globe (Rossel Papuan and Tseltal Mayan). Overall, we see general consistency in the distribution of object categories (e.g., consumables, mealtime tools, natural objects, etc.) handled by children across cultures and age, likely reflecting stable properties of children’s physical environments and day-to day routines. However, the exact objects available to children vary both within and across communities and diversify with age. These various distributions of handling patterns are discussed in their relation to potential consequences for early learning.

Understanding the trends and predictors of attrition rate, or the proportion of collected data that is excluded from the final analyses, is important for accurate research planning, assessing data integrity, and ensuring generalizability. In this pre-registered meta-analysis, we reviewed 182 publications in infant (0-24 months) functional near-infrared spectroscopy (fNIRS) research published from 1998 to April 9, 2020 and investigated the trends and predictors of attrition. The average attrition rate was 34.23% among 272 experiments across all 182 publications. Among a subset of 136 experiments which reported the specific reasons of subject exclusion, 21.50% of the attrition were infant-driven while 14.21% were signal-driven. Subject characteristics (e.g., age) and study design (e.g., fNIRS cap configuration, block/trial design, and stimulus type) predicted the total and subject-driven attrition rates, suggesting that modifying the recruitment pool or the study design can meaningfully reduce the attrition rate in infant fNIRS research. Based on the findings, we established guidelines on reporting the attrition rate for scientific transparency and made recommendations to minimize the attrition rates. We also launched an attrition rate calculator (LINK) to aid with research planning. This research can facilitate developmental cognitive neuroscientists in their quest toward increasingly rigorous and representative research.