English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Resource allocation is fundamental to a variety of societal decision-makingsettings, ranging from the distribution of charitable donations to assigninglimited public housing among interested families. A central challenge in thiscontext is ensuring fair outcomes, which often requires balancing conflictingpreferences of various stakeholders. While extensive research has beenconducted on theoretical and algorithmic solutions within the fair divisionframework, much of this work neglects the subjective perception of fairness byindividuals. This study focuses on the fairness notion of envy-freeness (EF),which ensures that no agent prefers the allocation of another agent accordingto their own preferences. While the existence of exact EF allocations may notalways be feasible, various approximate relaxations, such as counterfactual andepistemic EF, have been proposed. Through a series of experiments with humanparticipants, we compare perceptions of fairness between three widely studiedcounterfactual and epistemic relaxations of EF. Our findings indicate thatallocations based on epistemic EF are perceived as fairer than those based oncounterfactual relaxations. Additionally, we examine a variety of factors,including scale, balance of outcomes, and cognitive effort involved inevaluating fairness and their role in the complexity of reasoning acrosstreatments.

Epistemic vs. Counterfactual Fairness in Allocation of Resources