In medicine, there's a well-known maxim: never say more than your data allows. It's one of the first lessons learned by clinicians and researchers.
Journal editors expect it. Reviewers demand it. And medical researchers mostly comply. They hedge, qualify and narrow their claims often at the cost of clarity. Take this conclusion, written to mirror the style of a typical clinical trial report:
"In a randomized trial of 498 European patients with relapsed or refractory multiple myeloma, the treatment increased median progression free survival by 4.6 months, with grade three to four adverse events in 60 per cent of patients and modest improvements in quality-of-life scores, though the findings may not generalize to older or less fit populations."
It's medical writing at its most exacting and exhausting. Precise, but not exactly easy to take in.
Unsurprisingly, then, those careful conclusions often get streamlined into something cleaner and more confident. The above example might be simplified into something like: "The treatment improves survival and quality of life." "The drug has acceptable toxicity." "Patients with multiple myeloma benefit from the new treatment." Clear, concise but often beyond what the data justify.
Philosophers call these kinds of statements generics generalizations without explicit quantifiers. Statements like "the treatment is effective" or "the drug is safe" sound authoritative, but they don't say: For whom? How many? Compared to what? Under what conditions?
