How do native listeners process grammatical errors that are frequent in non-native speech? We investigated whether the neural correlates of syntactic processing are modulated by speaker identity. ERPs to gender agreement errors in sentences spoken by a native speaker were compared with the same errors spoken by a non-native speaker. In line with previous research, gender violations in native speech resulted in a P600 effect (larger P600 for violations in comparison with correct sentences), but when the same violations were produced by the non-native speaker with a foreign accent, no P600 effect was observed. Control sentences with semantic violations elicited comparable N400 effects for both the native and the non-native speaker, confirming no general integration problem in foreign-accented speech. The results demonstrate that the P600 is modulated by speaker identity, extending our knowledge about the role of speaker's characteristics on neural correlates of speech processing.

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A major goal in the early years of elementary school is learning to read, a process in which children show substantial individual differences. To shed light on the underlying processes of early literacy, this study investigates the interrelations among four known precursors to literacy: phonological short-term memory, vocabulary size, rhyme awareness, and trainability in the phonological specificity of lexical representations, by means of structural equation modelling, in a group of 101 4-year-old children. Trainability in lexical specificity was assessed by teaching children pairs of new phonologically-similar words. Standardized tests of receptive vocabulary, short-term memory, and rhyme awareness were used. The best-fitting model showed that trainability in lexical specificity partially mediated between short-term memory and both vocabulary size and rhyme awareness. These results demonstrate that individual differences in the ability to learn phonologically-similar new words are related to individual differences in vocabulary size and rhyme awareness

In lexical development, the specificity of phonological representations is important. The ability to build phonologically specific lexical representations predicts the number of words a child knows (vocabulary breadth), but it is not clear if it also fosters how well words are known (vocabulary depth). Sixty-six children were studied in kindergarten (age 5;7) and first grade (age 6;8). The predictive value of the ability to learn phonologically similar new words, phoneme discrimination ability, and phonological awareness on vocabulary breadth and depth were assessed using hierarchical regression. Word learning explained unique variance in kindergarten and first-grade vocabulary depth, over the other phonological factors. It did not explain unique variance in vocabulary breadth. Furthermore, even after controlling for kindergarten vocabulary breadth, kindergarten word learning still explained unique variance in first-grade vocabulary depth. Skill in learning phonologically similar words appears to predict knowledge children have about what words mean.

In this chapter, the analytical framework for popularization discourse is used to code the science journalism text “Baby Poop Is Loaded With Microplastics.” The chapter shows the kinds of insights that can be produced on the level of the individual text. Furthermore, presenting the in-depth analysis of a single text allows us to share what coding using our framework looks like on the level of the strategy.

In this concluding chapter, we look back on the contents of Re-presenting Research as a whole. We offer insight into the theoretical and applied insights that are generated through this book, which concern the framework itself, compliance with the aims that were set for the framework, the genre of popularization discourse as a whole, and applied insights. Options for further research are discussed, which include branching into other modes of popularization, focusing on the producer of popularization texts, the application of the framework in other settings, adding an evaluative component to the framework, and the construction of controversy in popularization discourse. Lastly, we offer some considerations for those readers wanting to develop their own analytical framework, whether it be to analyze popularization discourse or any other type of genre or text.

In this chapter, we introduce our own analytical framework for popularization discourse. The framework had to comply with four aims: be usable in any subgenre of popularization discourse, be usable in disciplinary and multidisciplinary/interdisciplinary settings, be reliable with multiple raters, and be easy to apply by offering application remarks and explanations of strategies. The analytical framework is produced through a construction and validation step. It consists of 34 strategies that are captured under five themes: Subject Matter, Tailoring Information to the Reader, Credibility, Stance, and Engagement. This chapter offers insight into these themes as well as into each individual strategy, for which application remarks and further reading suggestions are also offered. Lastly, the analytical framework is compared to existing frameworks and rubrics that were proposed in the academic literature.

This chapter presents the analysis of a corpus of 38 professional science journalism articles. The analysis is quantitative, that is, it shows how often each strategy is used in the corpus, and instrumental, which means that an interpretation of the texts is offered through the application of the analytical framework for popularization discourse. In this chapter, we include the percentage of use and an example of the use of each strategy. The median of strategy use is 20 (out of a possible 34), with a high score of 27 strategies and a low score of 10 strategies. Some strategies are used in (nearly) every text, such as presenting results/conclusions or hyperlinks, whereas other strategies are used hardly at all, such as references to popular lore and beliefs, and popular culture. Overall, strategies in the themes Subject Matter, Tailoring Information to the Reader, and Stance are used most, with the aggregated scores for the themes Credibility and Engagement being much lower. This analysis provides insights into how popularization strategies are used in a corpus of science journalism writing as a whole.