The complexity of individual graphemes is measured by means of the following method. Scanned versions of original Vai writing (from Appendix I) are first vectorised to ensure consistency of scale. On the vector images, two forms of complexity are calculated: perimetric complexity is the squared length of the inside plus outside perimeters of the grapheme, divided by the ink area contained within those perimeters, while algorithmic complexity is derived by compressing the vectorised image and measuring the file size.
In the second part of our study we will bring the Vai script into the laboratory. A few experiments are proposed with varying conditions. In one of these we ask participants to simply learn and then write out individual high-frequency Vai symbols with the output becoming the input for the next generation. In an alternative version we ask them to learn and reproduce whole words to test whether compositional effects of linear writing come into play. A variant experiment starts participants at different points in the history of the script. One group is trained on high-frequency characters as they were attested in 1834 and another group on the same set of characters as recorded in 1981. The prediction being that the 1981 characters will be less susceptible to change as they’ve already gone through the transmission bottleneck several times (when compared with the original 1834 script).
Predictions
For both parts of the study, our general predictions are the same:
1. Graphemes within the Vai character set will become more compressed over successive generations in both the graphic form of individual items as well as in the relationships between items.
This will be indicated by the following:
- Perimetric and algorithmic complexity of individual graphemes will decrease over successive generations
- Graphemes will become more self-similar. In other words, these items will come to be be generated from the same set of rules, resulting in typographic stereotypes (as for example, ‘stems’ in the Roman script ‘bowls’ and ‘lunettes’ in the Arabic script etc). Within character shapes, any repetitious forms will become abbreviated. In other words, standard repetitions will come to be inferred.
- Redundant graphemes (i.e. allographs representing the same syllable) will be eliminated in later generations
2. The Vai character set will exhibit greater speed of change in earlier generations than in later generations. In other words, there is a half-life for script change. The speed of change is measured by comparing time distance with complexity measures.
We expect to find that repeated transmissions of the script will amplify the compression bias, resulting in graphemes that are more compressed in later generations. For individual graphemes this can be described in terms of a principle of least effort, whereby the maximal amount of information is communicated by means of minimal graphic complexity. Likewise we expect system-wide compression, which will be observed when individual items act on one another systematically within the set, increasing the overall interdependence of the inventory.
If our predictions hold true, our study will represent the first validation that semiotic transmission experiments have explanatory relevance to the real-time evolution of a natural writing system, or indeed any known cultural phenomena.
-Are there typologies of script change? Eg, forms that are repeated an indeterminate number of times in a given grapheme, like waves in way lines, dots etc, will reduce. Eg, to four or less repetitions.