International Conference Balkan Languages and Dialects: Typology, Dialectometry, Corpus-Based Studies October 15–16, 2020 Institute for Linguistic Studies of the Russian Academy of Sciences (Saint Petersburg, Russia)

An atlas-based dialectometric approach to Cappadocian Greek

Stavros Bompolas University of Patras [email protected] Dimitra Melissaropoulou Aristotle University of Thessaloniki [email protected]

This paper reports on the first atlas-based dialectometric approach to geo-linguistic variation of Cappadocian Greek, an Asia Minor Greek variety spoken for great many centuries in a situation of regressive bilingualism due to intense contact with Turkish. Cappadocian Greek exhibits remarkable variation among its different communities and/or proposed dialectal zones (among others Dawkins 1916; Janse forthcoming), reflecting different degrees of archaisms and/or innovations, some of which — the latter — usually attributed to Turkish influence. Τhis dialectometric approach is elaborated within the frame of “DicaDLand”, a large-scale on- going research project on the Digitization of the Cappadocian Dialectal Landscape, aspiring to visualize, quantify, evaluate and account for the occurring intra-Cappadocian variation. Though numerous studies have taken advantage of the computerization of linguistic cartography (Lameli, 2010: 585–587), only few emphasize Greek (Ralli et al., 2010–2015, 2017–2018). Furthermore, to the best of our knowledge, this is the first dialectometric study on Greek dialectal data. To this end, we study the aggregate linguistic relationships among all — based οn data availability — Greek-speaking Cappadocian communities. Analysis emerges from a wide range of dialectal features drawn from all available written (and oral) sources, while different dialectometric methodologies are used to visualize different aspects of patterns (Nerbonne and Heeringa, 2010, for the different measurement tools we employ).

Figure 1: Fuzzy cluster dendrogram (top) and map (bottom) of Cappadocian dialects

International Conference Balkan Languages and Dialects: Typology, Dialectometry, Corpus-Based Studies October 15–16, 2020 Institute for Linguistic Studies of the Russian Academy of Sciences (Saint Petersburg, Russia)

Figure 1 shows the results of fuzzy clustering (Kleiweg et al., 2004; Nerbonne et al., 2008: 5) based on all attested phonological phenomena. Priority is given to phonological features, on the grounds that phonology has not drawn equal attention in studying intra-dialectal Cappadocian variation, while their visualization may be proved surprisingly revealing. It can be observed that the overall two-way split between northern (white-colored) and southern (pink-colored) Cappadocian is stable, following the existing literature. The resulting classification is mostly geographic, the main exception being the sub-variety of Delmeso, which is geographically southern but dialectologically northern (Dawkins, 1916: 10). However, the proposed dichotomy between western and eastern Cappadocian sub-zones is not fully supported by our findings, while central Cappadocian (Misti and Axo) does not emerge as a separate dialectal group. Moreover, Fertek and Ulaghatsh are not so closely related to the dialect groups they are supposed to belong to. Nevertheless, our first findings align with the dominant dialectological assumption that the dialects of Pharasa region (blue-colored) and Silli (green-colored) are separated from those of the Cappadocian mainland. The implementation of such a dialectometric approach is advantageous in that the areal distribution of language varieties is not pre-structured by linguistic assumptions underlying the selection of isoglosses, but it is generated from a huge set of data in which variation of forms in a single area is taken seriously into account. We aspire that additional research of the morphological, syntactic and lexical features will not only verify or counterargue the patterns of the traditional analyses (see Dawkins, 1916; Karatsareas, 2011; Janse, forthcoming; Tzitzilis, forthcoming), but also recognize further and more deeply entrenched patterns.

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