Many studies enacting LCT use diagrams to illustrate their analyses. Plotting research findings on diagrams such as specialization planes, semantic planes and autonomy planes provides an effective way to represent the relational characteristics of knowledge practices and affords a useful method to visualise changes in practices over time. Studies enacting the LCT dimension of Semantics often employ ‘semantic profiles’ to illustrate analyses, which essentially use simple line graphs to visualise shifts in strength of semantic gravity and semantic density over time. While this form of diagramming is an effective means of illustrating changes in strengths of variables over time, it is arguably less successful at representing the accumulation of variables – such as condensation of meaning – to the same extent.
Working specifically with the concept of epistemic-semantic density, this methodological-focused paper offers insights into a new method of visualising the accumulation of complexity of knowledge practices over time through a ‘complexity formalism’.
Unlike a semantic profile, which is an effective way to show the different strengths of epistemic-semantic gravity (ESG) or epistemic-semantic density (ESD) over time, the formalism is argued to be better able to represent the accretion of complexity as a text unfolds. It is especially useful for representing strategies of weaker ESD. When represented on a profile, the move down the y-axis to weaker ESD may be misinterpreted as a lack of complexity or that complexity is no longer being added. The formalism, in contrast, is able to show that even when weaker ESD strategies are enacted in writing, the preceding meanings that have been accumulated by that point are still carried forward (i.e. complexity is still being increased).
The formalism is a simple diagram that is governed by a straightforward, adaptable set of rules to suit the accompanying translation device. A single unit of meaning is represented by a single box. When meanings are related together, a connection is established between them. The type of connection that is established will depend on the translation device being used. This process of relating meanings together is represented by two boxes, which are connected by a particular kind of line. Depending on the type of relation established, the strength of the connection will be greater or weaker. When meanings that already hold technicality are added (such as a theoretical concept) the box representing that unit of meaning is shaded to reflect the increased complexity.
To illustrate how the formalism works and to demonstrate how it can be adapted to suit any translation device, two illustrative examples from doctoral writing are used. The first example will show how the formalism can be used in conjunction with Maton & Doran’s (2017) clausing tool to show the effects of the drafting process in doctoral writing. In particular, the formalism is used to show how doctoral candidates learn to build more complex knowledge more successfully through drafting. To illustrate this process, a formalism representing a draft text is compared to a formalism representing the final version of text.
The second example is taken from a history dissertation’s ‘findings’ chapter, which is written in a knower code. This illustrative example is used to demonstrate how the formalism can be adapted to suit a specific translation device for a specific object of study. It also reveals how the formalism is better able to represent small increments of complexity over time, which would typically be represented by a low semantic ‘flatline’ when using semantic profiles.
The methodological-focused paper offers other scholars who work with the concept of semantic density insight into how they can use the complexity formalism in their own research to diagram condensation of meaning in practices.
