In Multi-Criteria Decision Aiding, one of the current challenges involves the proper integration and tuning of the preference models in real-life contexts. In this article, we consider the multi-criteria sorting problem where the decision maker's preferences fall within the outranking paradigm. Following recent advances on extensions of classical majority-rule sorting models, we propose a methodology for adapting them to the perspective of the decision maker. We illustrate the application of the methodology on a real-world problem linked to the evaluation of contributors within Free/Libre Open Source Software communities. The experiments that we have carried out show that the various considered model extensions appear to be useful from the perspective of decision makers in a real-life preference elicitation process, and that the proposed methodology gives useful indications that can serve as guidelines for analysts involved in other elicitation processes.