Hedging is a behavior wherein speakers or writers attempt to distance themselves from the proposition they are communicating. Hedge terms include items such as ”I think X” or ”It’s sort of Y”. Identifying such behaviors is important for extracting meaning from speech and text, and can also reveal information about the social and power relations between the conversants. Yet little research has b...

Abstract Meta-analysis, the statistical analysis of results from separate studies, is a fundamental building block science. But assumptions classical meta-analysis models are not satisfied whenever publication bias present, which causes inconsistent parameter estimates. Hedges’ selection function model takes into account, but estimating and inferring with this tough for some datasets. Using gen...

This paper presents an effective and efficient approach for translating fuzzy classification rules that use approximative sets to rules that use descriptive sets and linguistic hedges of predefined meaning. It works by first generating rules that use approximative sets from training data and then translating the resulting approximative rules into descriptive ones. Hedges that are useful for sup...

We evaluated outcomes for 31 children with autism (2-6 years of age at intake) who received behavioral intervention in mainstream pre-school settings and a comparison group of 12 children receiving treatment as usual. After 2 years, children receiving behavioral intervention had higher IQ scores (Hedges g = 1.03 (95% CI = .34, 1.72) and adaptive behavior composite scores (Hedges g = .73 (95% CI...

In this paper we extend our previous results on sets of graded attribute implications with witnessed non-redundancy. We assume finite residuated lattices as structures of truth degrees and use arbitrary idempotent truth-stressing linguistic hedges as parameters which influence the semantics of graded attribute implications. In this setting, we introduce algorithm which transforms any set of gra...