☕ Nouveau Wikicafé la semaine prochaine !
On accueille @jsamwrites qui viendra parler de sa manière de wikifier la science dans son quotidien de chercheur.
L'occasion de découvrir Wikipédia abstraite, #Wikifunctions et de faire coucou à #Commons et #wikidata
> mardi 26 mai, 13h en visio ici :
https://fr.wikipedia.org/wiki/Projet:Wikifier_la_science/WikiCaf%C3%A9s
The Brazilian Scientific Research Information Ecosystem, #BrCris, is an aggregator platform that allows retrieving, certifying and visualizing data and information related to the various actors who work in scientific research in the Brazilian context.
Il #2aprile è la Giornata mondiale della consapevolezza sull’#autismo. Quanto contribuiscono i social all'awareness delle persone riguardo la #neurodivergenza?
Attraverso l'analisi di tre Instagram creator, quest'articolo di Susanna Bandi mette in luce come la piattaforma favorisca la costruzione di identità, la creazione di comunità e la diffusione di una comunicazione consapevole e inclusiva.
⬇️ In #openacess qui: https://riviste.unimi.it/index.php/AMonline/article/view/27242?mtm_campaign=mastodon
#SciX cannot control what arrangements publishers and authors have made between themselves. It can work with the community to promote #openscience and to help connect researchers with #openaccess versions.
#SciX makes it research #openacess whether publication or model or data.
#SciX respects the copyright of others.
Usage-based approaches to language acquisition emphasize the central role of input–output relationships in the gradual emergence of linguistic knowledge. Recent computational work has provided empirical support for this view by showing how network-based analyses can capture constructional patterns in child language. One such method is the Dynamic Network Model (DNM). However, it remains unclear whether these findings extend to bilingual acquisition, where differing input conditions across the two languages are expected to shape the formation of linguistic networks more visibly. To address this gap, the present study investigates two German–English bilingual children aged 2;03–3;11. Applying the DNM to both child-directed speech and children’s own utterances, we examine how constructional “pivots” emerge under bilingual input conditions and how they differ between individual children. Our results indicate that the DNM identifies informative clusters in the data, reflecting the language distribution in the input and thus provides a promising heuristic for advancing our understanding of bilingual first language acquisition.
Michael Pleyer
CAAInt.bsky.social
LSE Press
Institut für Deutsche Sprache
DMONTAGNE
Tel Amiel
Milano University Press
Jennifer Lynn Bartlett
Stefan Hartmann