Scientific Networks on Data Landscapes: Question Difficulty, Epistemic Success, and Convergence

Episteme 10 (4):441-464 (2013)
  Copy   BIBTEX

Abstract

A scientific community can be modeled as a collection of epistemic agents attempting to answer questions, in part by communicating about their hypotheses and results. We can treat the pathways of scientific communication as a network. When we do, it becomes clear that the interaction between the structure of the network and the nature of the question under investigation affects epistemic desiderata, including accuracy and speed to community consensus. Here we build on previous work, both our own and others’, in order to get a firmer grasp on precisely which features of scientific communities interact with which features of scientific questions in order to influence epistemic outcomes

Author Profiles

Patrick Grim
University of Michigan, Ann Arbor
Daniel J. Singer
University of Pennsylvania

Analytics

Added to PP
2013-12-12

Downloads
128 (#49,958)

6 months
27 (#37,567)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?