How we should measure orthographic depth: Or should we?

TL;DR

This paper explores how to measure orthographic depth, finding that different methods align with two key dimensions: unit size and mapping systematicity.

Contribution

The study introduces new approaches to quantify orthographic depth and clarifies how existing measures map onto theoretical dimensions.

Findings

Different measures of orthographic depth align with two underlying dimensions: unit size and systematicity.

New methods like distance-based measures and mutual information provide comparable results to existing ones.

Theoretical distinctions between complexity and unpredictability are reflected in the measurement outcomes.

Abstract

Cross-linguistic reading research often focuses on the effect of orthographic depth—the closeness of the relationship between print and speech. To understand its effect on reading, we need to be able to objectively quantify the level of orthographic depth of a given orthography. Previous work has suggested that different dimensions underlie orthographic depth, and it is not always clear if and how existing quantifications map onto these underlying dimensions. Here, we first examine how different measures relate conceptually to underlying theoretical dimensions. Then, we quantify the relative depth of eight European orthographies. We use existing methods and new approaches which have not been previously used to quantify orthographic depth: Distance-based measures relying on the closeness of the phonology of orthographically similar words, and mutual information, as a theory-neutral approach. The relationship between the different measures suggests that they map on two separate dimensions: the size of the orthographic units that map onto phonology and the systematicity of the mapping, in line with previous theoretical work which drew a distinction between complexity and unpredictability. The measures derived based on different theoretical assumptions largely show agreement. From a theoretical perspective, this prevents us from making differential predictions based on different approaches. From a practical perspective, this suggests that different measures may yield comparable results, as long as they tap into the same underlying dimension of orthographic depth.

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