Publication Date
9-14-2026
Digital Publisher
Digital Commons at St. Mary's University
Description
Visualizations can create an impression of immediacy: a pattern appears, an explanation follows, and managerial action can seem warranted before the transitions among observation, interpretation, judgment, and decision have been examined. This conceptual and pedagogical paper develops a Lonerganian Claim Audit for visual analytics, a discipline-specific adaptation of Bernard Lonergan's account of experience, understanding, judgment, and decision. It conceptualizes visual inferential compression as diminished differentiation among these operations, such that confidence generated by a visible pattern transfers to an explanation, an evidential claim, and an action without the distinct warrant required at each transition. The Claim Audit interrupts that movement by asking analysts to distinguish what is displayed from what is inferred, expose the assumption bridge supporting the first story, generate a credible rival explanation, classify the claim according to its evidential demands, and calibrate managerial action to the warranted claim, uncertainty, stakes, reversibility, and consequences for affected parties. A synthetic discount-and-sales example shows how an accurate aggregate visualization can invite an unwarranted causal story and an overextended recommendation. The paper then develops a pedagogical sequence built around first-story capture, peer challenge, visible revision, and interiority, and situates the framework within the Catholic Intellectual Tradition and Marianist educational context. The purpose is not to make analysts distrust visualizations, but to cultivate a more disciplined movement from seeing to understanding, judging, and acting.
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Collection
San Jose - Lonergan Chair in Catholic Philosophy
Format
Medium
Manuscript
Size
10 pages
City
San Antonio, Texas
Document Type
Article
Included in
Business Analytics Commons, Decision Science Commons, Educational Methods Commons, Scholarship of Teaching and Learning Commons