If you hear hoofbeats outside, it's probably a horse, not a zebra wearing a horse costume. When two stories both explain something, pick the simpler one — it's usually right, and it has fewer pieces to be wrong about.
Occam's Razor
When you have a few different explanations for something and they all fit the evidence equally well, pick the one that uses the fewest extra ideas. Adding more pieces — more secret causes, more invisible factors — doesn't make an explanation truer; it just gives it more places to be wrong. The rule is called Occam's Razor because it 'shaves off' anything you don't actually need. It's not about being lazy; it's about not making stuff up.
Occam's Razor
Parsimony, often called Occam's Razor, is the principle of preferring the simplest explanation that still accounts for the evidence. The medieval philosopher William of Ockham phrased it as 'entities should not be multiplied beyond necessity.' The idea isn't minimalism for its own sake — it's a discipline against adding parts, parameters, or assumptions that aren't doing real work. Modern science formalizes parsimony in tools like the Akaike and Bayesian Information Criteria, which automatically penalize models for using too many parameters, helping researchers avoid 'overfitting' — explanations that memorize the data instead of capturing the real pattern.
Parsimony, classically Occam's Razor, is the methodological preference for the simplest explanation, model, or theory that adequately accounts for the evidence at hand. William of Ockham's medieval maxim — entia non sunt multiplicanda praeter necessitatem (entities are not to be multiplied beyond necessity) — codified the principle. Modern formalizations ground it in Bayesian model comparison (marginal likelihood automatically penalizes complexity), information-theoretic criteria like AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion), Minimum Description Length (treating models as compressors of data), and Solomonoff induction based on Kolmogorov complexity (the length of the shortest program generating the data). A subtle point: different notions of simplicity — entity count, parameter count, description length, computational cost — can diverge, so any parsimony claim must specify which axis it is using and whether the preference is epistemic (a prior belief that simpler is truer) or pragmatic (simpler models are easier to test, communicate, and use).
- **Parsimony (Occam's Razor)** is not [**Essentialism**](../essentialism.md) because Parsimony prefers simpler explanations or models (fewer assumptions, lower complexity), whereas essentialism claims there exist necessary, immutable properties that define a thing's nature; one is a methodological principle, the other a metaphysical claim.
- **Parsimony (Occam's Razor)** is not [**Boundary Critique**](../boundary_critique.md) because Parsimony prioritizes minimal complexity in model construction, whereas boundary critique examines which assumptions and boundaries are implicitly embedded in existing systems; parsimony asks 'how few concepts?', critique asks 'whose framing?'.
- **Parsimony (Occam's Razor)** is not [**Minimalism**](../minimalism.md) because Parsimony is an epistemological principle favoring simpler explanations, whereas minimalism (in design, language, aesthetics) is a substantive choice to reduce elements or ornamentation; one governs how we reason, the other what we create.