Why do they call it "sampling distribution of the sample mean"? Ok, I understand that there is a true population mean and one that I get from the sample. It is different for every sample and, thus, I can build the distribution of the sample means. I arrive at a distribution of sample means. But why is it a sampling distribution? Is the whole point that the moniker must be longer than necessary? What do I lose if I omit the extra qualifier and get away with distribution of sample mean alone?
 A: For a given data set, the sample mean provides a single estimate of the population mean. This estimate is a constant and thus its distribution is rather boring. 
In contrast, the sampling distribution of the mean refers to the frequentist approach of considering the distribution of the sample means between many hypothesized samples drawn from the same population.
So it kind of makes sense to use a 'new' word.
A: Within a particular setting where the type of distribution is known or implied, "distribution of the sample mean" works just fine.  But in general would the "distribution of the sample mean" be its sampling distribution, a bootstrap distribution, a permutation distribution, or perhaps something else? 
The existence of different kinds of distribution of a sample statistic requires some linguistic method of disambiguation.  Without that, you lose precision and perhaps miscommunicate with your audience.
A: You can have a sampling distribution of other statistics than the mean, such as the estimated median, or estimated variance.
Sometimes "sampling distribution" might be a loose term referring to the estimated mean and estimated variance of the sample taken together (with the unspoken assumption that the distribution of sample means is approximately normal).
