In the summer of 2018, I set out to collect data for my master’s thesis (Tjuka 2019). The goal was to elicit body part terms that can also refer to object and landscape features. This was BC (before COVID-19), so I was able to meet with informants living in Berlin at the time and conduct my urban fieldwork study. The informants who participated in the study spoke one of 13 different languages (e.g., Wolof, Vietnamese, Czech). As a first task, I elicited 28 body part terms to get a sense of the naming patterns in each language. This blog post provides background information and introduces the resulting multilingual body part concept list.

Cross-linguistic studies of body terminology

The human body as a semantic domain has been a popular subject of study for cross-linguistic comparisons for many decades. In semantic typology, most studies focused on how languages segment the body into linguistic units (e.g., Enfield 2006). The studies revealed different naming strategies in the nomenclature of the human body. For example, the language Kuuk Thaayorre, spoken in Australia and belonging to the Paman languages of Cape York Peninsula, does not have a general term for the concept LEG or BODY (Gaby 2006). However, there seem to be naming strategies that occur across multiple languages (e.g., Andersen 1978). Since the samples used in cross-linguistic studies often neglect a certain geographic area or language family, Pattillo (2018) tested the regularity of the proposed universal patterns in 26 South American languages. She found that South American languages use structural similarity to extend body part terms to other body part terms, supporting Andersen’s (1978) claim that location and shape are common features for the extension of body part terms to analogous parts. Although one might assume that the body would be the perfect starting point for finding universals in semantics, these studies illustrate the diversity in how body parts are named. Hence, in my master’s thesis (Tjuka 2019), I wanted to make sure that I properly elicit the labels for relevant body parts before investigating their meaning extensions.

Eliciting body part terms across 13 languages

Speakers of 13 diverse languages participated in my study. They had grown up with one of the languages (e.g., Wolof, Vietnamese, Czech) as their first language and had learned English and/or German as a second language later in life. The languages included: Czech, Marathi, Persian, Greek, Vietnamese, Wolof, Mandarin Chinese, Khoekhoe, Hungarian, Japanese, Hebrew, Turkish, and  Malay (Bahasa Indonesia). To elicit the body part terms in each language, I used a line drawing (see picture below). Compared to coloring tasks in which participants color the area that refers to a specific body part term (see Van Staden and Majid 2006), I presented my informants with the line drawing on a tablet and pointed to one body part in the line drawing. They then responded which term in their native language was used for that part. This procedure was only applicable to external body parts (e.g., HEAD, ARM, LEG). For internal body parts (e.g., HEART, VEIN, RIB), I asked them if there was a term for that part in their first language.

The resulting list of 28 body part terms in 13 languages showed that Wolof, Czech, Marathi, and Greek colexify HAND and ARM.  Wolof, Czech, and Greek also colexify FOOT and LEG, as do Hungarian, Hebrew, and Malay. Interestingly, in a few languages, two terms were used to refer to the same body part, for example, in Czech pusa/ústa, and in Mandarin Chinese 嘴/口 refer to MOUTH. The body part list served as a reference point for the target stimuli of the study which consisted of 53 pictures of objects and landscapes that were based on 92 body part extensions (mainly found in English and German). In the main study (Tjuka 2019), the informants were asked whether they could refer to a highlighted part in the picture with a body part term.

Availability

The multilingual body part concept list with 28 items in 15 languages (including English and German as glossing languages) was converted into a CLDF data set (for more details about CLDF, see Forkel et al. 2018). This included publishing the data on a GitHub repository (https://github.com/cldf-datasets/tjukabodyparts) with additional metadata and specifications to ensure that the data is findable, available, interoperable, and reusable (FAIR, see Wilkinson et al. 2016). In addition, the list was linked to the Concepticon concept sets and released in Concepticon version 2.5.0 (ID: Tjuka-2019-28).

References

Andersen, Elaine S. 1978. Lexical universals of body-part terminology. In Joseph H. Greenberg (ed.), Universals of Human Language: Word Structure, vol. 3, 333–368. Stanford, California: Stanford University Press.

Enfield, Nicholas J., Asifa Majid & Miriam van Staden. 2006. Cross-linguistic categorisation of the body: Introduction. Language Sciences (Parts of the Body: Cross-Linguistic Categorisation, Special Issue) 28(2). 137–147. DOI:10.1016/j.langsci.2005.11.001.

Forkel, Robert, Johann-Mattis List, Simon J. Greenhill, Christoph Rzymski, Sebastian Bank, Michael Cysouw, Harald Hammarström, Martin Haspelmath, Gereon A. Kaiping & Russell D. Gray. 2018. Cross-Linguistic Data Formats, advancing data sharing and re-use in comparative linguistics. Scientific Data 5(1). 1–10. DOI:10.1038/sdata.2018.205.

Gaby, Alice R. 2006. The Thaayorre ‘true man’: Lexicon of the human body in an Australian language. Language Sciences (Parts of the Body: Cross-Linguistic Categorisation, Special Issue) 28(2). 201–220. DOI:10.1016/j.langsci.2005.11.006.

Pattillo, Kelsie E. 2018. Limb term naming patterns in South American languages. Anthropological Linguistics 60(4). 295–319. DOI:10.1353/anl.2018.0004.

Tjuka, Annika. 2019. Body-part metaphors as a window to cognition: A cross-linguistic study of object and landscape terms. Humboldt-Universität zu Berlin Master’s thesis. DOI:10.17613/j95n-c998.

Van Staden, Miriam & Asifa Majid. 2006. Body colouring task. Language Sciences (Parts of the Body: Cross-Linguistic Categorisation, Special Issue) 28(2). 158–161. DOI:10.1016/j.langsci.2005.11.004.

Wilkinson, Mark D., Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3(1). 1–9. DOI:10.1038/sdata.2016.18.

 

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