Cultural Consensus Theory: Aggregating Signed Graphs under a Balance Constraint

2012 ◽  
pp. 53-60 ◽  
Author(s):  
Kalin Agrawal ◽  
William H. Batchelder
Keyword(s):  
Cultural Consensus ◽  
Signed Graphs ◽  
Consensus Theory ◽  
Cultural Consensus Theory

Cultural Consensus Theory for the Evaluation of Patients’ Mental Health Scores in Psychiatric Detention Centers

2020 ◽  
Author(s):  
Don van den Bergh ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Mental Health ◽  
Practical Importance ◽  
Psychiatric Hospitals ◽  
Likert Scale ◽  
Cultural Consensus ◽  
Consensus Theory ◽  
Uncertainty Estimates ◽  
Cultural Consensus Theory ◽  
The Individual ◽  
As If

In many forensic psychiatric hospitals, patients’ mental health is monitored at regular intervals. Typically, clinicians score patients using a Likert scale on multiple criteria including hostility. Having an overview of patients’ scores benefits staff members in at least three ways. First, the scores may help adjust treatment to the individual patient; second, the change in scores over time allows an assessment of treatment effectiveness; third, the scores may warn staff that particular patients are at high risk of turning violent, either before or after release. Practical importance notwithstanding, current practices for the analysis of mental health scores are suboptimal: evaluations from different clinicians are averaged (as if the Likert scale were linear and the clinicians identical), and patients are analyzed in isolation (as if they were independent). Uncertainty estimates of the resulting score are often ignored. Here we outline a quantitative program for the analysis of mental health scores using cultural consensus theory (CCT; Anders & Batchelder, 2015). CCT models take into account the ordinal nature of the Likert scale, the individual differences among clinicians, and the possible commonalities between patients. In a simulation, we compare the predictive performance of the CCT model to the current practice of aggregating raw observations and, as an alternative, against often-used machine learning toolboxes. In addition, we outline the substantive conclusions afforded by the application of the CCT model. We end with recommendations for clinical practitioners who wish to apply CCT in their own work.

A Formal Method for Detecting and Describing Cultural Complexity

Field Methods ◽  
2018 ◽  
Vol 30 (3) ◽  
pp. 241-257 ◽  
Author(s):  
Michael G. Lacy ◽  
Jeffrey G. Snodgrass ◽  
Mary C. Meyer ◽  
H. J. Francois Dengah ◽  
Noah Benedict
Keyword(s):  
Formal Method ◽  
A Priori ◽  
Cultural Consensus ◽  
Cultural Groups ◽  
Cultural Complexity ◽  
Social Scientists ◽  
Formal Approach ◽  
Consensus Theory ◽  
Key Features ◽  
Cultural Consensus Theory

The most widely used formal approach to culture, the cultural consensus theory (CCT) of Romney, Weller, and Batchelder, originally relied on a priori definitions of cultural groups to map their unity and diversity. Retaining key features of classical CCT, we provide techniques to identify two or more cultural subgroups in a sample, whether those groups are known in advance or not. Our method helps CCT practitioners connect to contemporary approaches to culture in anthropology and related disciplines, which emphasize complexity. We suggest that our method provides reasonable and easily implementable approximations of cultural unity and diversity within a sample. In pursuing these matters, we contribute to other ongoing efforts to bring CCT closer to contemporary theorizing on cultural multiplicity, thus rendering CCT potentially more useful to a wider range of practicing social scientists.

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