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the claim

In science and everyday life, simple models are generally preferred over complex ones.

the verdict
SUPPORTED
the evidence backs this
Recorded sources
3 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that in science and everyday life, simple models are generally preferred over complex ones?

Yes. Simple models are generally preferred in science and everyday life because the principle of simplicity (Occam's razor) and optimal inference frameworks consistently balance model complexity against predictive accuracy.

Verdict: SUPPORTED · 3 sources for, 0 against · Last checked

The analysis

The claim is a specific, contestable, and empirical generalization about modeling choices in science and cognition, satisfying Step 0. Retrieved papers such as [1], [3], and [6] directly support the premise by detailing how Occam's razor and the trade-off between complexity and accuracy govern both human perception and scientific inference. No papers refute the general preference for simplicity as a principle, though some discuss specific contexts where trade-offs occur.

Evidence for · 3
2014
Explains that optimal Bayesian inference and model averaging explicitly trade off model complexity against accuracy.
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TH, F., RJ, D., & KJ, F. (2014). Model averaging, optimal inference, and habit formation.. doi.org. https://doi.org/10.3389/fnhum.2014.00457

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More for · 2
2016
Surveys the ubiquity of Occam's razor (simplicity principle) in perception, cognition, and probabilistic modeling.
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J, F. (2016). The simplicity principle in perception and cognition.. doi.org. https://doi.org/10.1002/wcs.1406

2023
Argues that Occam's razor is a foundational principle of science used to distinguish valid models from superstition.
Get citation
J, M. (2023). Razor sharp: The role of Occam's razor in science.. doi.org. https://doi.org/10.1111/nyas.15086

What does the evidence say?

The claim is a specific, contestable, and empirical generalization about modeling choices in science and cognition, satisfying Step 0. Retrieved papers such as [1], [3], and [6] directly support the premise by detailing how Occam's razor and the trade-off between complexity and accuracy govern both human perception and scientific inference. No papers refute the general preference for simplicity as a principle, though some discuss specific contexts where trade-offs occur.

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