Standard Grant: Productive Ambiguity in Classification

Arizona State University, Scottsdale AZ

Investigators

Abstract

This is a project in the history and philosophy of biology that has very substantial ramifications for data-intensive science. The PI will investigate how the history of taxonomy can shed new light on the value of ambiguity for science in the domain of data-intensive science. The project focuses on detecting trade-offs in the value of ambiguity for scientific language as a function of changing social contexts. Accurate disambiguation relies on a shared background of knowledge and abilities, which may prove inadequate as concepts spread into new contexts or a community grows larger and more heterogeneous. The project will fund graduate and undergraduate research assistants to analyze a text corpus drawn from two centuries of history in biological taxonomy. It will also support public events and the creation of educational materials addressing the theme of productive ambiguity in naming and classification. This project will implement an integrative conceptual framework enabling empirical investigation of ambiguity in linguistic settings. It will use an information-theoretic framework from cognitive pragmatics to quantify ambiguity in a way that is open-ended enough to accommodate a wide range of phenomena shaping human language and communication while also reflecting the specific constraints required by computers. It will provide novel tools for tracking changes in language at the level of populations rather than individuals while remaining sensitive to underlying social institutions and individual differences. Results from this project will open new perspectives on the history of types and subspecies in systematics, and it will inform contemporary debates about the virtues of maximal determinacy in the computational representation of human language and meaning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.