Abstract: The present paper advocates for incorporating Big Team Science practices into the language sciences. Big Team Science is a promising mode of collaborative research in which top-down coordina...

ALT: Barney Stinson Hmmmmmm

Abstract: The present paper advocates for incorporating Big Team Science practices into the language sciences. Big Team Science is a promising mode of collaborative research in which top-down coordination directs efforts by a large number of researchers from different institutions towards a common scientific goal. The redistribution of resources and division of labor enabled by Big Team Science may enable researchers to increase methodological rigor, systematically explore claims across a wider sample of languages, and to diversify both the languages studied and the researchers engaged. However, implementing Big Team Science practices is not without challenges, some of which are unique to the language sciences. We suggest strategies and best practices for adapting to these challenges, including theoretical and methodological pluralism, variation in conditions among data collection sites, and navigating a trade-off between maximizing methodological rigor and ability to engage with the most inclusive, typologically broad language samples.

Building cumulative knowledge in the language sciences through reproducible, robust, and replicable research findings

Science publishing–like all of science–requires money. There’s no getting around it, even with the open science movement. What appears free to many authors and readers still requires money and infr…

When psychological researchers investigate binary outcomes, they routinely report odds ratios to quantify the strength of an effect or an association. This is quite understandable given that psycholog...

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Get updates about when and where we launch our online course on data communication.