Phd in DOCUMENTATION STUDIES, LINGUISTICS AND LITERATURE

Thesis title: Sequenzialità e simultaneità nella LIS. Dagli articolatori ai significanti

Language, whether spoken or signed, is intrinsically connected to the community that uses it: both are mutually constructed and influenced. This relationship is particularly complex in the case of sign languages, which develop within often invisible communities—lacking territorial connotation and subject to prejudice, stereotypes, and linguistic deprivation. This thesis explores Italian Sign Language (LIS) through the analysis of sequentiality and simultaneity phenomena, with the aim of highlighting the structural peculiarities of the signed linguistic system. An annotation methodology was developed to detect the activity of manual and bodily articulators, applied according to three segmentation criteria: Hands LIN-H, Any LIN-A, and Time LIN-T. Hands LIN-H (manual linearity) tracked the activation and modification of manual articulators only; Any LIN-A (linearity of any articulator) tracked the activation and modification of both bodily and manual articulators; and Time LIN-T (temporal linearity) followed a predefined time-based segmentation. Using this methodology, four videos of spontaneous LIS were analyzed, differing in text type (monologues and dialogues) and context (in-person and remote). The thesis is structured into three parts: a theoretical section, which frames the relationship between language and community, particularly focusing on the concepts of iconicity and arbitrariness; a methodological section, which describes the process of data collection and coding; and an analytical section, which presents the qualitative and quantitative results of the segmentations along with their discussion. The comparison among the three segmentation methods revealed that Any (LIN-A) provides the most accurate linguistic representation, both qualitatively and quantitatively. It identified a greater number of segments and signifiers and was able to capture phenomena that were not observable with the other segmentation methods. The analysis identified thirteen types of segments, grouped into two macro-categories: linear segments (two types) and simultaneous segments (eleven types). Simultaneity was found to be predominant across all texts, and within the segment sequences, variations in the number of signifiers and the redistribution of active articulators were observed. The results offer a rich and detailed understanding of the structure of the analyzed texts and the architecture of Italian Sign Language (LIS).