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 platform 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 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 of lexemes 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 combination 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, and how
classifiers are tied with reference tracking.
9. Studying verb classification, and identifying the semantic relations and comparing them to the argument structure of the studied language.