Cognitive aspects of lexical availability

Abstract

Lexical availability measures the ease with which a word can be generated as a member of a given category. It has been developed by linguistic studies aimed, among other things, at devising a rational basis for selecting words for inclusion in dictionaries. The measure accounts for the number of people who generated a given word as a member of a designated semantic category and the position in which they produce the word. We present an analysis of lexical availability from a cognitive perspective. Data were analysed for Spanish speakers generating words from five semantic categories—clothes, furniture, body parts, animals, and intelligence. Six properties of words were investigated as potential predictors of lexical availability. Predictors were concept familiarity, typicality, imageability, age of acquisition, word frequency, and word length. Categories differed on these variables, and regression analysis found concept familiarity, typicality, and age of acquisition to be significant predictors of lexical availability. The cognitive basis of these findings and the practical consequences of selecting words on the basis of lexical availability are considered.

We thank Alberto Carcedo González for his help and Professors Julio Borrego Nieto, José Antonio Bartol, Rosario Llorente Pinto, Emilio Prieto de los Mozes, and Javier de Santiago Guervós of the University of Salamanca for their invaluable assistance with this study which forms part of the project El léxico disponsible del hablante hispano: aportación de datos y replanteamiento teórico and was supported by the Grant Ministerio de Ciencia y Tecnología (BFF2001-1005).

Notes

¹The suitability of the AoA measure has been a constant matter of concern. Zevin and Seidenberg (2002, 2004) have recently argued that the high correlations between age of acquisition and so many other factors (word frequency, familiarity, imageability, word length, concreteness, and number of neighbours) causes great difficulty when investigating the unique/singular influence of AoA in lexical tasks. They proposed a new operationalisation of AoA related to the frequency with which words are experienced through different ages. In their view, early acquired words are those whose frequency of trajectory through life starts very high during infancy to steadily decrease through the years. The opposite, words of low frequency in childhood that increase their frequency through time, constitutes late acquired words. This AoA measure, called frequency of trajectory, has been found to influence object naming and lexical decision times (Bonin, Barry, Méot, & Chalard, 2004; Zevin & Seidenberg, 2004). Frequency of trajectory correlates highly with AoA only, representing (at least in part) the AoA variable independently of other factors. Despite this, frequency of trajectory is not free from problems. Firstly, it reduces age of word learning to written frequency of exposure knowing that other factors (concept familiarity, imageability, word length, number of neighbours, and spoken word frequency) also contribute when a word is learnt (Bonin et al., 2004; Zevin & Seidenberg, 2002). Secondly, the way in which early and late acquired words are understood (having different frequency of trajectories through time) excludes the great majority of the words in the vocabulary, that is, those words experienced with an equal or similar frequency over the years. Finally, although the operationalisation of late acquired words as having low to high frequency of trajectory might be appropriate, most early acquired words do not have high to low trajectories. Only words related to the fantastic world such as giant, ogre, and fairy have higher frequencies in a child's language than in adults. Generally, early learned words retain into adulthood the frequencies they had in childhood. Nevertheless, and despite its problems, it would have been interesting to see the predictor power of frequency of trajectory on the category generation task. Unfortunately, there is not a reliable database providing word frequencies for the different schooling years of Spanish children. For this reason we were unable to include frequency of trajectory as another predictor in the analysis.