SOAS Research Online

A Free Database of the Latest Research by SOAS Academics and PhD Students

[skip to content]

Dohle, Ebany (2020) Nahuat-Pipil: The Encoding of Ecological Knowledge in Semantic and Lexical Categorisation Systems. PhD thesis. SOAS University of London. DOI: https://doi.org/10.25501/SOAS.00037843

[img]
Preview
Text - Submitted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND 4.0).

Download (6MB) | Preview

Abstract

This thesis investigates the encoding of natural world knowledge by analysing folk nomenclature and folk classification systems of plant knowledge (Berlin 1992) within the Nahuat-Pipil language of El Salvador. Furthermore, it establishes how the possession of traditional ecological knowledge (TEK) for speakers of the language is a key component of indigenous identity, and how historical events and experiences affect the use and perception of the Nahuat-Pipil language amongst Indigenous people. It was found that cognitive categorisation practices appear both overtly within the lexicon of the language as well as covertly. The findings of the interdisciplinary field-based research are contextualised within Nahuat-Pipil history and social context to better understand the relationship between ecological knowledge and notions of identity. This research into the categorisation of plants draws on theories from Cultural Linguistics (Sharifian 2017), Linguistic Relativity and Cognitive Linguistics , in addition to theories and methods from Ethnobiology (Berlin 1992; Martin 2007) and Anthropology (Davies 2008). It has used semi-structured and topic led interviews, as well as ethnographic and experimental methods to gather data. Finally, the use of an interdisciplinary and community-led approach to language documentation brings into question the roles and relationships between community, language, documentation and revitalization.

Item Type: Theses (PhD)
SOAS Departments & Centres: Departments and Subunits > School of Languages, Cultures & Linguistics
SOAS Research Theses
Supervisors Name: Peter Austin
DOI (Digital Object Identifier): https://doi.org/10.25501/SOAS.00037843
Date Deposited: 11 Aug 2022 10:31
URI: https://eprints.soas.ac.uk/id/eprint/37843

Altmetric Data

Statistics

Download activity - last 12 monthsShow export options
Downloads since deposit
6 month trend
165Downloads
6 month trend
133Hits
Accesses by country - last 12 monthsShow export options
Accesses by referrer - last 12 monthsShow export options

Repository staff only

Edit Item Edit Item