Integrative Complexity Coding Raises Integratively Complex Issues

Datos Bibliográficos

ID6336702
AutoresPhilip E Tetlock (0000-0002-6535-530X, University of Pennsylvania), Emlen Metz (0000-0001-5401-6508, University of Pennsylvania), S Emlen Metz (University of Pennsylvania), E Scott (0000-0002-8992-5936, University of Pennsylvania), Sydney E Scott (University of Pennsylvania), Peter Suedfeld (0000-0003-2563-036X, University of Pennsylvania)
Año2014
Volumen35
Número5
Páginas625-634
Fecha de publicación2014-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaPolitical Psychology (JOURNAL)
Identificadores de la revistaISSN: 0162-895X • E-ISSN: 1467-9221
EditorialWiley (PUBLISHER • GB)
DOI10.1111/pops.12207
OpenAlexW1961166401
IdiomaEN
Citas recibidas15
Referencias citadas41

Conway, Conway, Gornick, and Houck (2014) report a major effort to automate integrative complexity coding. Judging this effort requires researchers to be more explicit in articulating key methodological assumptions about the coding process and theoretical assumptions about the construct. Unresolved issues include: (1) when, and on what basis, we should attribute divergences between human coders and algorithms to overestimations or underestimations by one or the other approach; and (2) to what extent second‐generation algorithms can yield Pareto improvements that reduce errors of both underestimation and overestimation. Further progress in developing natural language processing measures of this cognitive style will require sharper definitions of target constructs: in particular, different types of differentiation (dialectical and elaborative) and integration (hierarchical and flexible) and clearer guidelines for factoring context into assessments

Coding (social sciences · Cognitive science · Context (archaeology · Dialectic · Epistemology · Factoring · Statistics · Computer Science · Decision-Making and Behavioral Economics · Explainable Artificial Intelligence (XAI · Mathematics · Psychology · Topic Modeling · Theoretical Computer Science