On the fractal nature of complex syntax and the timescale problem

Abstract

Fundamental to complex dynamic systems theory is the assumption that the recursive behavior of complex systems results in the generation of physical forms and dynamic processes that are self-similar and scale-invariant. Such fractal-like structures and the organismic benefit that they engender has been widely noted in physiology, biology, and medicine, yet discussions of the fractal-like nature of language have remained at the level of metaphor in applied linguistics. Motivated by the lack of empirical evidence supporting this assumption, the present study examines the extent to which the use and development of complex syntax in a learner of English as a second language demonstrate the characteristics of self-similarity and scale invariance at nested timescales. Findings suggest that the use and development of syntactic complexity are governed by fractal scaling as the dynamic relationship among the subconstructs of syntax maintain their complexity and variability across multiple temporal scales. Overall, fractal analysis appears to be a fruitful analytic tool when attempting to discern the dynamic relationships among the multiple component parts of complex systems as they interact over time.

The complexity epistemology and ontology in second language acquisition: A critical review

“…DST assumes that “specific patterns of variation may be inherent in complex systems and that large changes are part of these patterns; as such, large changes do not need a specific explanation, or at any rate not more than small changes” (de Bot, 2008, p. 174). This idea that smaller changes are the mirror image of larger changes echoes the concept of “fractality” in CT, that patterns of small and large changes are self-similar or, put simply, the same mechanisms work on all scales, in a complex system (see, e.g., Evans, 2020).…”

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“…Beyond basic repeated-measures designs, even when treating time as a continuous dimension, the time window adopted is more an artifact of study design rather than a genuine indicator of the actual timescale of change (de Bot, 2015;Maie & Godfroid, 2023). It may be that various measures of the quality of L2 production that are in widespread use develop on different time scales necessitating the use of multiple, hierarchical temporal levels of analysis (Evans, 2020). For instance, supraclausal measures may develop more rapidly than subclausal measures of complexity, or vice versa.…”

Complex adaptive interventions: The challenge ahead for instructed second language acquisition research

“…That is, logistical constraints may dictate when data are collected, irrespective of hypothesized developmental timelines. In fact, it may be that various outcome measures of L2 learning that are in widespread use develop on different time scales, necessitating the use of multiple hierarchical temporal levels of analysis (Evans, 2020).…”