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RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

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Computational Universalism, or, Attending to Relationalities at Scale.

Francis Lee^1,2, David Ribes³

¹Media Technology, Södertörn University, Stockholm, Sweden.

Social Studies of Science

|July 14, 2025

Summary

Scholars adopting computational terms risk obscuring computation's universalizing aims. Examining translation efforts reveals how computational actors create connections, but also their exclusions and partialities.

Keywords:

algorithm computation data domain platform universalism

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Area of Science:

Social Sciences
Humanities
Computational Studies

Background:

Increasing adoption of computational terminology in social sciences and humanities.
Risk of obscuring universalizing practices by focusing on vernacular computational objects (e.g., data, algorithms, AI) and specific domains (e.g., finance, health, governance).

Purpose of the Study:

To problematize the uncritical adoption of computational categories in research.
To highlight how these categories can act as epistemic traps, naturalizing computational universalism.
To propose an alternative approach focusing on the labor of translation and commensuration.

Main Methods:

Critical analysis drawing on intellectual traditions that question universalizing claims.
Examination of how computational actors establish relationalities across scales and boundaries.
Focus on the processes of translation and commensuration enabling computational interventions.

Main Results:

Computational categories can obscure the universalizing ambitions of computation.
These categories naturalize the expanding reach of computational universalism.
An alternative approach reveals both the achievements and the exclusions/partialities of computational relationalities.

Conclusions:

Scholars should move beyond accepting hardened computational categories.
Attending to the effortful work of translation and commensuration offers a more nuanced understanding.
This perspective illuminates the labor behind computational universalism and its inherent limitations.