The Conceptual Distinctions between Statistically Correlated and Theoretically Connected Variables

DISCriminability: A Model for Understanding the Conceptual Distinctions between Statistically Correlated and Theoretically Connected Variables.

Lecturer: Adam Galinsky, Columbia Business School

Adam Galinsky

Adam Galinsky. Photo: Colombia Business School

About the lecture

The current analysis presents the DISCriminability Model for understanding the conceptual distinctions between statistically correlated and theoretically connected variables. The DISCriminability Model (Discriminate through Definitions-Interactions-Sources-Consequences) highlights how researchers can discriminate between two related variables by exploring their Definitional distinctions, the Interaction between them, their discrete Sources, and their disparate Consequences.

We first explore the DISCriminability Model in the context of positively correlated variables. For positively correlated variables, placing them into a factorial 2X2 conceptual space reveals unique and often unnoticed phenomena in the off-diagonals (i.e., high X but low Y or low X but high Y): the Little Tyrant Effect of power without status, the Sociopath Effect of perspective-taking without empathy, the Robin Hood Effect of unethical behavior without selfishness, the Model Minority Effect of prejudice with positive stereotypes, the Sleazy Salesperson effect of passion without authenticity. Here we also highlight the DISCriminability of the Big Five Personality factors, where each sub-facet is theoretically connected but conceptually distinct.

We next explore the DISCriminability Model in the context of negatively correlated variables. For negatively correlated variables, placing them into a factorial 2X2 conceptual space reveals unique phenomena in the high-high cell (i.e., high X and high Y): the Nostalgia Effect of happiness and sadness; the Tough Love Effect of candidness and sensitivity; the Generous Narcissist Effect of self and other focus.

Overall, the DISCriminability Model offers a framework for creating a deeper understanding of our social world, while offering a roadmap for young scholars who want to provide theoretically novel insights and for fields that want to achieve optimized parsimony. model also has the potential to generate new practical solutions and efficient treatments.

Published Jan. 4, 2017 12:11 PM - Last modified Apr. 3, 2018 2:24 PM