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This paper aims to analyse dialectal data by using a variationist approach. The goal is to show both the nature and the distribution of innovative features among different groups of speakers, focusing on the so-called Italianization of the dialects (ID), i.e., the reduction of their structural distance from Italian (Sobrero1997, Ricca 2010, Scivoletto 2014, and Cerruti 2016).
Data come from fieldwork carried out in 30 localities in the north-western Italian region of Piedmont. 120 informants were interviewed, selected on the basis of such sociolinguistics variables as age, sex, and geographical origin. Data were collected by using two different methodologies, namely: the recording of spontaneous speech, and a translation involving 40 sentences. The process of ID is investigated with respect to both morphology and syntax, in order to access whether, and to what extent, the dialects react to the pressure exerted by Italian.
The first part of the paper provides a brief discussion of the concepts of both Italianization and convergence (see, e.g., Berruto 2005, Røyneland 2010, and Cerruti/Regis 2014). Then, the methodology employed to analyse the data, namely the Multiple Correspondence Analysis (MCA), is presented. MCA is a statistical tool which allows for the identification of systematic relationships between variables: for the purposes of this work, I employed the function MCA from the package FactoMineR of the software R. It is worth underlining that the use of such a methodology is quite new for dialectological studies, since it is traditionally used to observe patterns of variation in standard languages (see for example Cerruti/Vietti 2022 for spoken Italian).
The product of the analysis is a coordinate system in which the variables display an irregular distribution. In fact, MCA shows that some innovative features are clustered together, while others are located in the same area of the graph as the traditional ones, suggesting the presence of a form of composite variety peculiar to the Italo-Romance contact situation. Consistent with that, not only the vertical, downward diffusion of Italianized features emerges, but also phenomena of horizontal contact, between dialectal varieties, show up.
By using MCA, it is possible to both detect and map variation within the community under scrutiny, as well as to correlate the main on-going tendencies with both specific categories of speakers (e.g., semi-speakers, cfr. Dorian 1981 and Grinevald/Bert 2011) and sociolinguistic characteristics of the interviewed. This type of approach may indeed provide a new perspective on the data, though a qualitative analysis is needed to support MCA; some examples are thus discussed from a qualitative standpoint.