automated integrative complexity coding

[Larsen, Jeff T]

Hello everyone –

 

This just came through on the SPSP listserv:

Dear colleagues,

As many of you know, our lab developed a tool to measure integrative complexity in an automated fashion (AutoIC). It is free for academic use and can be accessed at autoic.org. If you are looking for a way to score integrative complexity that doesn't take a lot of time, AutoIC might be a useful option for you.

Validity information on the system, as well as lists of publications that have used the system, can be accessed at autoic.org. Thanks!

Best,

--Luke

------------------------------
Lucian (Luke) Gideon Conway III
luke....@umontana.edu

 

I’ve long thought that Sudfeld and Tetlock’s notion of integrative complexity could shed a lot of light on attitudinal ambivalence. Whereas most of us (including me!) rely on rating scales, getting at integrative complexity involves careful analysis of participants’ written texts.  Here’s a bit from Wikipedia:

Integrative complexity is a research psychometric that refers to the degree to which thinking and reasoning involve the recognition and integration of multiple perspectives and possibilities and their interrelated contingencies.

Integrative complexity is a measure of the intellectual style used by individuals or groups in processing information, problem-solving, and decision making. Complexity looks at the structure of one's thoughts, while ignoring the contents. It is scorable from almost any verbal materials: written materials, such as books, articles, letters, and transcript; as well as audio-visual material.

The measure of integrative complexity has two components: differentiation and integration. Differentiation refers to the perception of different dimensions when considering an issue. Integration refers to the recognition of cognitive connections among differentiated dimensions or perspectives.^[1]

 

The idea of doing manual IC coding has always been daunting. The availability of automated IC coding could open a lot of doors.

 

-- Jeff

 

**********************
Jeff T. Larsen, Ph.D.
Professor of Psychology

University of Tennessee, Knoxville
jeff....@utk.edu  /    google voice: 865-315-7927

 

[Iris K. Schneider]

Hi Jeff, 

Somehow I missed this post, but this is really cool! I have some old datasets where we asked people to write about an ambivalent topic or non ambivalent topic - maybe trying out whether this analyses differentiates between texts written under each of these prompts might be an interesting first step.

Thanks for sharing, 

Iris