Florence A. R. Oxley

Introduction: Nursery rhymes, which are rich in literary devices, benefit children's language learning. Less is known about the influence that nursery rhymes' messages may have on children's development. We focused on “Monday's Child,” a popular nursery rhyme that alleges children's day of the week of birth forecasts their differences in personality and physical traits. Methods: Data came from E‐Risk, a UK population representative, longitudinal cohort study of 2232 same‐sex twin children (with 93% retention). We used linear regression models to test whether the day of the week of birth predicted personality and physical traits at ages 5–18 years. Results: Being born on Monday through Saturday did not predict children's personality and physical traits as implied by the “Monday's Child” rhyme. Being born on Sunday was also not associated with children's traits across measures. These results were unchanged after covariate adjustment (i.e., children's sex, birthweight, and socioeconomic status). Conclusion: We showed that children's differences in personality and physical traits are independent of their day of the week of birth. These findings suggest that nursery rhymes' messages are unlikely to influence children's development, at least those conveyed by “Monday's Child”.

Nursery rhymes are rich in alliteration and vocabulary, and their benefits for children’s language and literacy have been widely studied. Less is known about the influence that nursery rhymes’ messages may have on children’s development. Here, we focused on ‘Monday’s Child’, a popular nursery rhyme which alleges that the day of the week of children’s birth forecasts their differences in physical and psychological traits. Data came from E-Risk, a UK-population representative, longitudinal cohort study of 1,116 families, whose same-sex twin children were assessed at ages 5 through to 18 years (with 93% retention). In our preregistered analyses, being born on Monday through Saturday did not predict children’s physical and psychological traits as implied by the ‘Monday’s Child’ rhyme (β = -.04 to .03; 95%CI = -0.10 to 0.09; p = .195 to .754). Being born on Sunday was also not associated with children’s traits across measures (β = -.00; 95%CI = -0.05 to 0.05; p = .945). Results were unchanged after covariate adjustment (i.e., children’s sex, birthweight, and socioeconomic status). Our findings suggest that children’s differences in physical and psychological traits are independent of the day of the week of their birth, refuting the messages from ‘Monday’s Child’ nursery rhyme.

Adulthood is traditionally inferred from the socio-demographic milestones of marriage, parenthood, and having a stable, long-term career. Yet today these milestones are often delayed or unattainable for young people. We conducted a meta-analysis of studies using the Markers of Adulthood scale across the past three decades to assess (a) endorsement rates (%) of marriage, parenthood, and career as markers of adulthood, and (b) whether people think they have reached adulthood. Across 39 samples ( N = 17,465), marriage and parenthood were endorsed by a quarter of participants, whereas career was endorsed by 57%, suggesting that in today’s society career defines adult status more than marriage and parenthood. Furthermore, half of emerging adults (aged 18–29 years) considered themselves to have reached adulthood despite traditional milestones of adulthood occurring less frequently and later in life than ever before. Our findings have three main implications for measuring adult status including (1) deemphasise on the socio-demographic milestones of marriage and parenthood; (2) include wider age ranges in research; and (3) explore cultural differences. Reducing the focus on socio-demographic milestones and including more diverse samples will improve our understanding of adulthood and advance adults’ identity development.

Intelligence is polygenic, highly heritable, and predicts wide-ranging life outcomes. Here, we meta-analysed the predictive validity of polygenic scores for intelligence based on the largest available genome-wide association study (or GWAS; Savage et al., 2018) for tested, phenotypic intelligence to date. Across 32 estimates from 9 independent samples, which all came from WEIRD countries and were of European ancestry (Ntotal=452,864), our meta-analytic estimate for the association between polygenic and phenotypic intelligence was ρ=.245 (p<.001, 95% CI=.184 – .307), an effect of medium size. The meta-analytic estimate varied across samples, studies, and phenotypic measures of intelligence, and even after accounting for these moderators, polygenic score predictions remained significantly heterogenous. Our findings support claims that polygenic predictions of intelligence benefit and advance research but their utility in other contexts is yet to be demonstrated.

Intelligence is polygenic, highly heritable, and predicts wide-ranging life outcomes. Here, we meta-analysed the predictive validity of polygenic scores for intelligence based on the largest available genome-wide association study (or GWAS; Savage et al., 2018) for tested, phenotypic intelligence to date. Across 32 estimates from 9 independent samples, which all came from WEIRD countries and were of European ancestry (Ntotal=452,864), our meta-analytic estimate for the association between polygenic and phenotypic intelligence was ρ=.245 (p<.001, 95% CI=.184 – .307), an effect of medium size. The meta-analytic estimate varied across samples, studies, and phenotypic measures of intelligence, and even after accounting for these moderators, polygenic score predictions remained significantly heterogenous. Our findings support claims that polygenic predictions of intelligence benefit and advance research but their utility in other contexts is yet to be demonstrated.

Intelligence is polygenic, highly heritable, and predicts wide-ranging life outcomes. Here, we meta-analysed the predictive validity of polygenic scores for intelligence based on the largest available genome-wide association study (or GWAS; Savage et al., 2018) for tested, phenotypic intelligence to date. Across 32 estimates from 9 independent samples, which all came from WEIRD countries and were of European ancestry (Ntotal=452,864), our meta-analytic estimate for the association between polygenic and phenotypic intelligence was ρ=.245 (p<.001, 95% CI=.184 – .307), an effect of medium size. The meta-analytic estimate varied across samples, studies, and phenotypic measures of intelligence, and even after accounting for these moderators, polygenic score predictions remained significantly heterogenous. Our findings support claims that polygenic predictions of intelligence benefit and advance research but their utility in other contexts is yet to be demonstrated.

Adulthood is traditionally defined by the socio-demographic milestones of marriage, parenthood, and having a stable, long-term career. Yet today these milestones are typically delayed or unattainable for young people. We conducted a meta-analysis of studies using the Markers of Adulthood scale across the past three decades to assess (a) endorsement rates (%) of marriage, parenthood, and career as markers of adulthood, and (b) whether people think they have reached adulthood. Across 39 samples (N = 17,465), marriage and parenthood were endorsed by less than 25% of participants, whereas career was endorsed by 58%, suggesting that in today’s society career defines adult status more than marriage and parenthood. Furthermore, half of emerging adults (aged 18-29 years) considered themselves to have reached adulthood despite traditional milestones of adulthood occurring less frequently and later in life than ever before. Our findings have three main implications for researchers measuring adult status: These are to (1) focus less on the socio-demographic milestones of marriage and parenthood; (2) include wider age ranges in research; and (3) explore cultural differences. Reducing focus on socio-demographic milestones and including more diverse samples will allow us to better understand adulthood and provide support for adults’ identity development and psychological well-being.

This chapter reviews the literature relating to teaching and learning the language of mathematics and presents key feature and keywords analyses in the Key Stage 2 (KS2) and Key Stage 3 (KS3) mathematics sub-corpora. Key feature analysis showed that the language of KS2 and KS3 mathematics teaching reflects the current guidance and policy for mathematics education with regard to topics like comparison and algebra. Mathematical symbols, nominalisations and gerunds/present participles were found to be more frequent in the KS3 mathematics sub-corpus than in the KS2 mathematics sub-corpus. KS3 mathematics is more multisemiotic and involves more abstract language than KS2 mathematics. Keywords analysis showed that KS3 mathematics relied on polysemous words that were used with domain-specific meanings, abstract concepts and more phrasal language features to a greater extent than KS2 mathematics. These features of language require complex processing and may be unfamiliar to many secondary students in Year 7. This constellation of complex linguistic features may make accessing mathematics more challenging for students at the beginning of secondary school.

In this chapter, the key findings of the book are summarised. The themes that have recurred across all the studies have been register, polysemy, purpose and context. The overall challenge of these for students starting secondary school is considered and ways forward for research are suggested. The project continues to work with school practitioners to develop awareness and consider implications for the transition years.

This chapter presents a review of literature on the language of science teaching and analysis of polysemy in the Key Stage 2 (KS2) and Key Stage 3 (KS3) science sub-corpora. Understanding the language of science is valuable for education, but also for participation in civil life. Scientific language allows for efficient and precise thought and talk about very specific objects and phenomena and the complex relationships between them. However, many students – and possibly many adults – find the language of science alienating and inaccessible. Like mathematics, science is multisemiotic, so requires students to be able to ‘translate’ information between modalities. Previous research has focused on the unfamiliar, technical and polysemous vocabulary of science, and on how grammar and discourse structure is used to create informationally dense texts and talk that have a sense of authority and objectivity. The analyses presented here show that there is a very large increase in the number of new words and meanings encountered in KS3 compared with KS2. Polysemy with everyday meanings of words varies in degree but is extremely common overall.