Creating an 100(1-a)% interval estimate of the population mean based on the sample's mean and variance is equivalent to examining the set of all values which produce a p-value below a%. Your view of the way Alice and Bob should be making inference about the true mean is actually exactly what hypothesis testing is. It's just that there is often a "status quo" belief about the parameter which has important theoretical implications. And academic papers are usually about that belief specifically, so it makes sense that they talk about it as a "hypothesis test". And that's the logical headline, the statement about the specific value. But standard deviations and distributions are often given, making it trivial to create the interval as a reader.