• 2019
• 2018
• 2017
• 2016
• 2015
• 2014
• 2013
• 2012
• 2011
• 2010
• 2009
• 2008
• 2007
• 2006
• 2005
• 2004
• 2003
• 2002
• 2001
• 2000
• 1999
• 1998
• 1997
• 1996
• 1995
• 1994
• 1993
• 1992
• 1991
• 1990
• 1989

Publication Summary and Abstract

Crowe, S. J. and T. J. Prescott (2003), Continuity and Change in the Development of Category Structure: Insights from the Semantic Fluency Task, International Journal of Behavioural Development, 27: 467-479.

Children aged between 5 and 10 years old were tested on a semantic fluency (freelisting) task for two categories: animals and body parts. Additive tree analysis (Sattath & Tversky, 1977) was used to clusters items based upon both their proximity in the generated lists and their frequency of co-occurrence; the resulting trees together with production frequency data were compared across three age groups. For the animals category, this analysis revealed that although older children named proportionally more non-mammals, at all ages children tend to cluster animals according to their environmental context. For body parts, the analysis showed more parts, particularly internal organs, named with age and a cluster of face parts generated by all age groups. A novel feature of the current research was the use of statistical measures of additive tree similarity. The results are discussed with respect to theories of developmental change in the organization of conceptual memory, and are viewed as supporting an assumption of continuity with age in the use of schematic relations in category structure. Insights are drawn from connectionist modeling to help explain the persistence, throughout childhood, of early forms of memory organization.

Matlab code for calculating the Fowlkes and Mallows (1983) B(k) statistic for comparing two additive trees is provided below.

Note: An improved metric for calculating normalised inter-item distances is described in Prescott et al. 2006, and is recommended in place of the α component of the αβ metric described here.

Erratum: On p. 470. In the equation for α(a, b). The parameter λ(nalnbl) should be a divisor not a multiplier of dabl. Note that this is corrected in the preprint version available for download below.

Locally hosted preprint
Matlab code for the Fowlkes and Mallows (1983) B(k) statistic