Whether we consider a factor fixed or random is more about how the researcher thinks about the factor rather than what the design actually looks like. Let’s say I run a study with 100 participants in 2 conditions. If I want to generalize my results to people other than the particular 100 people I ran in my study, then subjects should be random. But if the 100 people in my study are 100% of the population I’m interested in (e.g. I want to know how members of this psych department behave under condition A vs. condition B, and I run all of us in the experiment), then subjects is fixed. It still looks the same on the surface (100 people in two conditions), but the way we conceptualize the design is different. Similarly, if you test 4 emotions, that could be fixed or random, depending on how you want to generalize your results. If these four emotions are the only ones you want to know about, then they’re fixed. If these are a sample from a larger population of emotions, and you want to generalize to that population, then they’re random. The study looks the same on the surface in both cases (testing people under each of the four emotions included in your study), but the design and the EMS table change.

This has implications for replication attempts. If you wanted to replicate one of my example studies above, the way you would replicate it depends on whether the factors are fixed or random. If you want to replicate my finding about how members of this psychology department perform under condition A vs. condition B, then you should use the same exact people I did again (the members of this psychology department). But if you’re interested in generalizing the results to a larger population (academic psychologists in general, perhaps), then you could and should use a new sample from that population. Similarly, if you want to replicate my findings about how people behave under different emotions, whether you use the exact same 4 emotions I used depends on whether the study is actually about those 4 emotions and no others, or if it’s about emotions in general and I just happened to pick those 4 examples. If you want to generalize to a larger population of emotions, then you could and should draw a new sample of emotions to test.

All that matters is whether you want to generalize to some larger population or not.