The Archaeology of The Mind Lab studies how different cultures, past and present, organize knowledge about the world. Our sources are classifier systems that appear in both written and oral languages around the world. Classifiers, which arrange the lexicon into various emic categories, have never been scrutinized systematically for the study of knowledge organization.
Our research addresses the following topics:
1. Identifying the category that each classifier heads and defining its structure — The central members and the fuzzy-edge members in each category.
2. Getting closer to emic lexical meanings by defining the range of categories to which a lexical item is assigned.
3. Studying multiple classification of a single host, and identifying compatibility patterns and classifier-order patterns.
4. Assessing classifier centrality in culture — Classifiers that head large categories versus those that head small ones.
5. Metadata searches — Studying classifier assignment by script, time, geography and other variables annotated for each token in the iClassifier database.
6. Researching the longue durée — How do classifier categories emerge and how do they decline?
7. “Classifying the Other,” an analysis of the classification of loanwords — How productive is a classifier system?
8. Studying the lexical, pragmatic and meta-textual usages of classifiers.
9. Studying verb classification, and identifying the semantic relations and comparing them to the argument structure of the studied language.
iClassifier is a digital research platform designed to analyze classifier systems in detail. Through a data-mining process we undertake relational pattern recognition with the aim of identifying governing rules as well as of documenting each language studied. The iClassifier research app is expected to contribute significantly to a greater understanding of classification processes and knowledge maps in each culture’s “mind.” We hope, on the one hand, to point to universal cognitive patterns that are shared by all cultures, and on the other hand, to identify culture-specific patterns in each case study.
Our data model is compatible with the Thot Data Model (TDM, cf. Polis & Razanajao 2016) and our metadata are based on the ‘Thesauri and ontology for documenting Ancient Egyptian Resources (THOT, http://thot.philo.ulg.ac.be).