Chenzi Xu

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.

Local differentiation and innovation in spoken Mandarin are now ubiquitous in metropolises in China, accelerated by the widespread promotion of the national lingua franca Standard Mandarin. This paper examines the lexical tones of Plastic Mandarin, a newly crystallised urban Mandarin dialect in Changsha, where the dominant regional variety has been Changsha Xiang. This paper establishes the lexical tone system for Plastic Mandarin using Growth Curve Analysis and explores its development by comparing its tones with those of Changsha produced by the same group of multilingual speakers, employing Generalised Additive Mixed Modelling. The findings show that, while Plastic Mandarin shares the same tone categories as Standard Mandarin, it features distinctive f0 patterns, some of which closely resemble their corresponding Changsha tones. These f0 patterns, imbued with regional identity, are likely motivated by phonetic variation, systemic constraints, social biases, and language contact. The case of Plastic Mandarin may exemplify contact-induced tonal contour changes in forming new Mandarin varieties.

The study of citation tones, lexical tones produced in isolation, is one of the first steps towards understanding speech prosody in tone languages. However, methodologies for investigating citation tones vary significantly, often leading to limited comparability of tone inventories, both within and across languages. This paper presents a systematic review of research methods and practices in 136 citation tone studies on 129 tonal language varieties in China, including 99 studies published in Chinese, which are therefore not easily available to an international scientific readership. The review provides an overview of possible analytical decisions along the research pipeline, and unveils considerable variation in data collection, analysis, and reporting conventions, particularly in how f0, the primary acoustic correlate for tone, is operationalised and reported across studies. Key methodological issues are identified, including small sample sizes and inadequate transparency in communicating methodological decisions and procedure. This paper offers a clear road map for citation tone production research and proposes a range of recommendations on speaker sampling, experimental design, acoustic processing techniques, f0 analysis, and result reporting, with the goal of facilitating future tonal research and enhancing resources for underrepresented tonal varieties.

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis that can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling but also from decisions regarding the quantification of the measured behavior. In this study, we gave the same speech-production data set to 46 teams of researchers and asked them to answer the same research question, resulting in substantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further found little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise, or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system, and calibrate their (un)certainty in their conclusions.