Manipulations of outcome favorability and outcome fairness are frequently treated as interchangeable, and assumed to have redundant effects. Perceptions of outcome fairness and outcome favorability are similarly presumed to have common antecedents and consequences. This research tested the empirical foundation of these assumptions by conducting a meta-analytic review of the justice literature (...

Liveness/Fairness plays an important role in software specification, verification and development. Existing event-based compositional models are safety-centric. In this paper, we describe a framework for systematically specifying and verifying event-based systems under fairness assumptions. We introduce different event annotations to associate fairness constraints with individual events. Fairne...

We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and span the range from group fairness to strong individual fairness. We study the accuracy-fairness trade-off on any given dataset, and we measure the severity of this trade-off via a numerical quantity we call the Price of...

The main objective of this paper is to propose a more efficient, distributed, and multi-objective billing model that can be implemented in every smart meter the grid for achieving optimality fairness. First, we develop new evaluation index evaluate such as not only addressing fairness but also minimize cost reduce Peak-to-Average Ratio (PAR) load demand subsequently bill each customer. Then, st...

In wireless networks many nodes contend for available resources creating a challenge in resource allocation. With shared resources, fairness in allocation is a serious issue. Fairness metrics have been defined to measure the fairness level of resource decisions in allocations. Therefore, fairness metrics significantly influence network and node performances emphasizing the need for due diligenc...

Competency-based medical education systems allow institutions to individualize teaching practices to meet the needs of diverse learners. Yet, the focus on continuous improvement and individualization of curricula does not exempt programs from treating learners in a fair manner. When learners fail to meet key competencies and are placed on probation or dismissed from training programs, issues of...