Final answer:
Fairness can be statistically or empirically determined depending on the context, such as with fair dice in gambling or the distribution of resources in markets. Empirical evidence is used to examine if an event is fair, unbiased, and has equal likelihood of outcomes or if there are disparities that indicate unfairness.
Step-by-step explanation:
Issues of fairness can be determined statistically or empirically depending on the context (C). Fairness in a statistical sense often relates to whether or not an event, process, or characteristic is free of bias and holds equal likelihood for various outcomes. For instance, in gambling or games, fair dice should have an equal chance of landing on any number, otherwise game outcomes are not fair. Similarly, when considering a broader societal context, statistical and empirical methods can assess fairness, for example, by inspecting if there's an equal distribution of resources or opportunities for different groups of people.
Empirical evidence plays a crucial role in determining fairness, much like the example of the Belgian one-euro coin mentioned, where repeated trials suggested that the coin was not fair because heads came up more often than tails. In economics, the fairness of markets in reaching equilibrium can involve complex interactions between efficiency and equity, and certain trade-offs may exist. Here, empirical data can assess whether a market's equilibrium indeed reflects fairness in terms of resource distribution and opportunity cost.