How you define your research variables has a profound impact on research outcomes. This is particularly true with social, political-science and psychological research, where taxonomies are critical to the categorization and analysis of data: Psychological research depends on the DSM V definitions, for example, while political and social sciences research is frequently dependent on concepts/constructs such as ethnicity, nationality, religiosity and sexual orientation.
This project seeks to determine whether a common machine learning algorithm will identify cohorts similar to those used by PSOT researchers in their research projects, when presented with the data-sets used by PSOT researchers.
This project is a side investigation of a much bigger research project, which is an analysis of whether identity (religion, sexual orientation and/or ethnicity), contingency (wrong place / wrong time) or the political activity of victims of torture has any predictive power as to the intensity of survivor’s levels of psychological trauma (specifically PTSD and depression) and / or the arc of their recovery.
The machine learning project is a way of testing the assumption that the categories of identity, contingency and activity have any relevance at all to the clinical history of our clients.
Background
In 2008 I began a project to duplicate the technique(s) found in “Nude Descending a Staircase” using Max/MSP and any solo-dance video.
Theory
For theory, you can refer to Edward Fry’s beautiful book Cubism for a “canonical” approach to cubism. There are a dozen copies at the Strand.
Method
My approach to cubist video employs the following techniques:
All of these components can be found in Duchamps and Picasso. Video allows for more complicated implementations of more or less the same ideas.
This project is quite well advanced, but is being done under the auspices of the Program for Survivors of Torture. When I am finally authorized to publish the work, I will post a link here. Contact me if you are interested in this project.