The traceback method and the early constructicon: theoretical and methodological considerations

Abstract

Usage-based approaches assume that children’s early utterances are item-based. This has been demonstrated in a number of studies using the traceback method. In this approach, a small amount of “target utterances” from a child language corpus is “traced back” to earlier utterances. Drawing on a case study of German, this paper provides a critical evaluation of the method from a usage-based perspective. In particular, we check how factors inherent to corpus data as well as methodological choices influence the results of traceback studies. To this end, we present four case studies in which we change thresholds and the composition of the main corpus, use a cross-corpus approach tracing one child’s utterances back to another child’s corpus, and reverse and randomize the target utterances. Overall, the results show that the method can provide interesting insights—particularly regarding different pathways of language acquisition—but they also show the limitations of the method.

Traceback and Chunk-Based Learning: Comparing Usage-Based Computational Approaches to Child Code-Mixing

“…This can be seen as evidence in favor of the hypothesis that the usage-based model of language acquisition can also account for code-mixed data, as language-mixed utterances can be analyzed as instances of either fixed chunks or frameand-slot patterns. However, as pointed out in various TB studies before, as well as in methodologically oriented papers (see e.g., Hartmann et al 2021;Koch et al 2020), the method has a number of limitations. Perhaps most importantly, not all of the patterns identified via TB can be assumed to be psychologically plausible.…”

“…below; also seeKoch et al 2020). Still, a number of studies have shown that regardless of the exact implementation, a large proportion of target utterances can be successfully traced back (see e.g., D ąbrowska 2014; D ąbrowska and Lieven 2005; Vogt and Lieven 2010; for Italian, see Miorelli 2017; for German, see Koch 2019; for critical evaluations of the method, see Koch…”

Building languages: Estonian–English two-year-old bilingual’s reliance on patterns in code-mixed utterances

“…Furthermore, Hartmann, Koch & Quick (2021:8) note that 'this essentially limits the application of ADD to vocatives like mommy or adverbials like now and then'. Koch, Hartmann & Quick (2020) explain that if the target utterance is will das haben Mama 'wanna have that Mummy', and will das haben can be derived and the algorithm also finds that Mama meets the frequency threshold, then the derivation is considered to be successful. The reason for the restriction is the desire to avoid implausible derivations (Dabrowska & Lieven 2005).…”

“…In the corpus of this study there were about 1,000 more monolingual child utterances than code-mixed utterances, which likely has an effect on the method's ability to find patterns. The idea that the size of the corpus is a factor influencing the traceback results has been suggested by Koch, Hartmann & Quick (2020), who summarized and analyzed the limitations of the method. Based on the data from four German-speaking children, they found that the child with the smallest test corpus also has high traceback results while the child with the largest test corpus has low traceback results.…”

The Building Blocks of Child Bilingual Code-Mixing: A Cross-Corpus Traceback Approach

“…This suggests that in essence, the same patterns that account for children's monolingual language use can also account for their code-mixing. In the present study, we extend this analysis, combining it with a cross-corpus traceback approach as proposed in Koch et al (2020). While we only relied on utterance-initial ngrams in Quick et al (2019), the computational implementation of the traceback algorithm in this paper is closer to the original traceback method, although it is still simplified in order to allow for a fully automatic analysis 3 .…”