Degrees of strength: not just strong or weak
A common beginner mistake is to treat inductive strength as binary — either 'strong' or 'weak' with nothing in between. In practice, inductive arguments fall along a continuum. A survey of three friends is weaker than a survey of 300 random participants, which in turn is weaker than a meta-analysis of 30 studies spanning multiple countries. Learning to place arguments on this continuum is a core skill.
To make this more precise, consider five rough grades. Very weak: the evidence barely supports the conclusion (tiny sample, obvious bias, no controls). Weak: there is some evidence, but significant gaps remain. Moderate: the evidence is decent but not conclusive — there are identifiable weaknesses that could be addressed. Strong: the evidence is broad, relevant, and well-matched to the claim, with only minor reservations. Very strong: the evidence is extensive, diverse, and methodologically rigorous, and the conclusion is proportionately hedged.
Using a graded scale forces you to articulate exactly what pushes an argument up or down the continuum. Is it the sample size? The representativeness? The number of rival explanations that have been ruled out? The fit between the conclusion's language and the evidence's scope? Each of these factors adjusts the grade, and being able to name the adjusting factor is what separates an informed evaluation from a gut reaction.
Side-by-side comparison makes grading easier. When you encounter a new argument, find a benchmark: an argument you have already graded that shares some features. Ask whether the new argument is stronger or weaker than the benchmark, and why. Over time, you build a mental library of calibrated examples that makes new evaluations faster and more consistent.
- Place the argument on a continuum rather than assigning a binary label.
- Name the specific factors that determine the grade.
- Compare to a benchmark argument when possible.
- Remember that 'moderate' is a perfectly legitimate and common grade.
Takeaway: Inductive strength is a spectrum, and naming where an argument falls — and why — is more useful than a binary verdict.