Mechanistic Modeling for the Masses

Turner, Matthew A.; Smaldino, Paul E.

doi:10.31234/osf.io/8pj9n

“…Watts, 2011). The result is that theories in the social and behavioral sciences are rarely articulated with enough precision or supported by enough evidence for researchers to be sure which parameters are relevant and which can be safely ignored (Berkman & Wilson, 2021;Meehl, 1990b;M. A. Turner & Smaldino, 2022;Yarkoni, 2020).…”

Section: The Problem With the One-at-a-time Paradigmmentioning

confidence: 99%

“…In other words, the human world is vastly more complex than the physical one, and researchers should be neither surprised nor embarrassed that their theories about it are correspondingly less precise and predictive (Watts, 2011). The result is that theories in the social and behavioral sciences are rarely articulated with enough precision or supported by enough evidence for researchers to be sure which parameters are relevant and which can be safely ignored (Berkman & Wilson, 2021;Meehl, 1990b;Turner & Smaldino, 2022;. Researchers working independently in the same domain of inquiry will therefore invariably make design choices (e.g., parameter settings, subject pools) differently Gelman & Loken, 2014).…”

Section: The Problem With the One-at-a-time Paradigmmentioning

confidence: 99%

Beyond Playing 20 Questions with Nature: Integrative Experiment Design in the Social and Behavioral Sciences

Almaatouq

¹

,

Griffiths

²

,

Suchow

³

et al. 2022

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The dominant paradigm of experiments in the social and behavioral sciences views an experiment as a test of a theory, where the theory is assumed to generalize beyond the experiment's specific conditions. According to this view, which Alan Newell once characterized as “playing twenty questions with nature,” theory is advanced one experiment at a time, and the integration of disparate findings is assumed to happen via the scientific publishing process. In this article, we argue that the process of integration is at best inefficient, and at worst it does not, in fact, occur. We further show that the challenge of integration cannot be adequately addressed by recently proposed reforms that focus on the reliability and replicability of individual findings, nor simply by conducting more or larger experiments. Rather, the problem arises from the imprecise nature of social and behavioral theories and, consequently, a lack of commensurability across experiments conducted under different conditions. Therefore, researchers must fundamentally rethink how they design experiments and how the experiments relate to theory. We specifically describe an alternative framework, integrative experiment design, which intrinsically promotes commensurability and continuous integration of knowledge. In this paradigm, researchers explicitly map the design space of possible experiments associated with a given research question, embracing many potentially relevant theories rather than focusing on just one. The researchers then iteratively generate theories and test them with experiments explicitly sampled from the design space, allowing results to be integrated across experiments. Given recent methodological and technological developments, we conclude that this approach is feasible and would generate more-reliable, more-cumulative empirical and theoretical knowledge than the current paradigm—and with far greater efficiency.

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“…In other words, the human world is vastly more complex than the physical one, and researchers should be neither surprised nor embarrassed that their theories about it are correspondingly less precise and predictive (Watts, 2011). The result is that theories in the social and behavioral sciences are rarely articulated with enough precision or supported by enough evidence for researchers to be sure which parameters are relevant and which can be safely ignored (Berkman & Wilson, 2021;Meehl, 1990b;Turner & Smaldino, 2022;. Researchers working independently in the same domain of inquiry will therefore invariably make design choices (e.g., parameter settings, subject pools) differently Gelman & Loken, 2014).…”

Section: The Problem With the One-at-a-time Paradigmmentioning

confidence: 99%

The elephant's other legs: What some sciences actually do

Baron

2024

Behav Brain Sci

0

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Integrative experiments, as described, seem blindly empirical, as if the question of generality of effects could not be understood through controlled one-at-a-time experiments. But current research using such experiments, especially applied research, can resolve issues and make progress through understanding of cause–effect pathways, leaving to engineers the task of translating this understanding into practice.

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