Statistical inference without frequentist justifications

Statistical inference is often justified by long-run properties of the sampling distributions, such as the repeated sampling rationale. These are frequentist justifications of statistical inference. I argue, in line with existing philosophical literature, but against a widespread image in empirical science, that these justifications are flawed. Then I propose a novel interpretation of probability in statistics, the artefactual interpretation. This interpretation is able to bridge the gap between statistical probability calculations and rational decisions on the basis of observed data. The artefactual interpretation is able to justify statistical inference without making any assumptions about probability in the material world.