Fairness Considerations Research Articles

Value Loss in Allocation Systems with Provider Guarantees

Many operational settings share the following three features: (i) a centralized planning system allocates tasks to workers or service providers, (ii) the providers generate value by completing the tasks, and (iii) the completion of tasks influences the providers' welfare. In such cases, the planning system's allocations often entail trade-offs between the service providers' welfare and the total value that is generated (or that accrues to the system itself), and concern arises that allocations that are good under one metric may perform poorly under the other. We propose a broad framework for quantifying the magnitude of value losses when allocations are restricted to satisfy certain desirable guarantees to the service providers.} We consider a general class of guarantees that includes many considerations of practical interest arising, e.g., in the design of sustainable two-sided markets, in workforce welfare and compensation, or in sourcing and payments in supply chains, among other application domains. We derive tight bounds on the relative value loss, and show that this loss is limited for any restriction included in our general class. Our analysis shows that when many providers are present, the largest losses are driven by fairness considerations, whereas when few providers are present, they are driven by the heterogeneity in the providers' effectiveness to generate value; when providers are perfectly homogenous, the losses never exceed 50\%. We study additional loss drivers and find that less variability in the value of jobs and a more balanced supply-demand ratio may lead to larger losses. Lastly, we demonstrate numerically using both real-world and synthetic data that the loss can be small in several cases of practical interest.

Price Discounts and Customized Product Assortment under Multinomial Logit Choice Model: A Robust Approach

With increasing availability of consumer data and rapid advancement and applications of technologies, online retailers are gaining better knowledge of shopping behavior and preferences of their customers. Thus more and more retailers are providing customized product assortment to better match the needs of customers and generate more sales. In this paper, we study a two-stage revenue management model where a retailer decides non-customized price discounts at stage one due to fairness consideration and customized product assortment at stage two (upon the arrival of customers) under the multinomial logit choice model. We employ a robust approach for the joint discounts and customized assortment optimization problem to handle data uncertainty for estimating customer preferences and distribution of different customer segments. We analyze the structural properties of the problems and propose efficient computational methods to solve the problems with/without cardinality constraint on the assortment. In certain cases, our algorithm converges at a superlinear rate. When there is a cardinality constraint on the assortment, we find the retailer should offer deeper discounts as the constraint becomes more restrictive. We also provide some discussion on the value of our robust solution and the extension when the customer discount sensitivity function is also uncertain. Finally, our extensive numerical study shows that the solutions under the robust approach perform very well compared to the one assuming accurate information and has robustness when there is uncertainty.

Priority setting and personal health responsibility: an analysis of Norwegian key policy documents

BackgroundThe idea that individuals are responsible for their health has been the focus of debate in the theoretical literature and in its concrete application to healthcare policy in many countries....

Doping, Debunking, and Drawing the Line

ABSTRACT The current ban on certain performance enhancing substances in sport such as erythropoietin (EPO) faces a line-drawing problem: what is the moral difference between taking an EPO injection to increase one’s hematocrit and using an hypoxic chamber to the same end (supposing that they involve similar health risks)? The standard approach to this issue is to evaluate various arguments for banning certain substances and methods – arguments based on considerations of fairness, coercion, harm, naturalness, etc. I take a different approach which considers prospects for attempts to use evolutionary debunking arguments (EDAs) to address the line-drawing problem and resolve the tension between different normative judgments that we may be disposed to have about the use of EPO and hypoxic chambers. I consider three different considerations on which an anti-doping evolutionary argument (ADA) might be based, and I argue that, due to certain facts about the nature of psychological dispositions and the vagueness of judgments to which they give rise, no such argument can be used to address the line-drawing problem. I also discuss how the difficulties for these debunking arguments bear on WADA’s ``spirit of sport‘’ criterion as it might be called upon to help settle the matter of which substances are to be banned. Finally, I briefly consider what our inability to explain away condemnation of doping via ADAs might tell us about the origin of anti-doping intuitions and what it suggests about the proper approach to anti-doping policy.

Distributional impact of corporate extraction and (un)authorised clandestine mining at and around large-scale copper- and cobalt-mining sites in DR Congo

Analyses of conflict between large-scale mining (LSM) and artisanal and small-scale mining (ASM) in the provinces of Haut-Katanga and Lualaba, southeastern Democratic Republic of Congo (DRC) should take into account the equity and fairness considerations linked to the enforcement of the property rights of corporate and other actors. There is a growing empirical record on the negative distributional consequences of LSM companies’ takeover of mining concessions in the DRC. Also considered by some authors, albeit less examined in the literature, is the distributional impact of mechanisms for clandestine extraction from mine sites taken over by LSM firms. Despite common assumptions about ASM being beyond the control of government authorities to tax or regulate, clandestine mining at LSM sites, and the transport of minerals out of these sites, is frequently authorised and informally and efficiently taxed by security forces and other gatekeepers. Despite the pervasiveness of authorised clandestine mining and the frequent use of force to enforce its rules and regulations, artisanal miners also resist such practices and engage in unauthorised clandestine mining – without the knowledge of the security forces, or by using aggressive tactics to bypass them. The key argument in this piece is that arrangements and processes for clandestine extraction, whether authorised or unauthorised, should not simply be viewed as constituting corruption and a conflict risk, but also have distributional effects, including some positive implications in terms of local resource distribution. This article, which focuses on those who rely, directly or indirectly, on ASM, is based on qualitative research in the DRC over seven and a half months from August 2016-May 2017 at two case-study sites in Haut-Katanga and one in Lualaba.

Self‐managed work teams: An efficiency‐rationale for pay compression

AbstractThis paper uncovers a novel mechanism through which pay dispersion can have a negative effect on firm performance, even in the absence of equity or fairness considerations. We use a stylized model of a self‐managed work team to show that, when team‐work involves heterogeneous tasks, the provision of incentives to exert effort conflicts with the provision of incentives to share information relevant for decision‐making. Pay dispersion deteriorates information sharing as it induces workers to conceal “bad news” to maintain their coworkers motivation. The practical implications of our theory are that team empowerment should go hand in hand with pay compression and that empowerment should be avoided when team production involves strongly heterogeneous tasks.

Keep your enemy close? Competitive online brands’ expansion with individual and shared showrooms

Showroom locating is a recent practice implemented by online brands to address the customers’ need for trying a product before making a purchase. Showrooms are shown to stimulate sales and enhance customer engagement. In this study, two competitive online brands’ showroom expansion and pricing decisions are jointly analyzed. First, given showroom decisions, we investigate the equilibrium prices and discuss the implications of different showroom configurations on the prices, demands, and profits of the brands. It is shown that a brand’s showroom expansion can hurt as well as benefit the other brand. After that, the equilibrium expansion with individual showrooms is characterized when the expansion decisions are made sequentially or simultaneously. We also characterize how the equilibrium decisions change depending on a showroom’s impact on the brands’ market potentials. Finally, a shared showroom concept is examined and cost-sharing contracts for sharing a showroom are introduced based on a brand’s initiation, bargaining, and fairness considerations. The findings imply that sharing a showroom can increase total profits. Furthermore, it is possible that a brand can incentivize the other brand to share a showroom.

Saudi females' buying behavior of green cosmetics: A pertinent motivational aspect

ABSTRACT The study investigates which group of Saudi females are more conscious about buying green cosmetic products. It also analyses the relationship between motivational factors (MF), purchase preferences (PP), and tendency towards heath consciousness (THC) in green cosmetic products. A model was developed to understand the influence of independent variables on the dependent variable. MF, PP, and THC were considered as independent variables and purchase of green cosmetic products as dependent variable. A survey was conducted using a survey questionnaire and collected data from 318 Saudi women under three major segments (university students, working women, and non-working women) belonging to various provinces in Saudi Arabia. Multiple regressions in SPSS software were used to analyze the collected data. While the students do not have a significant purchasing capability, housewives lack an informed purchasing decision. However, only the working women are potentially motivated with fair health consciousness and consideration to purchase the green cosmetics. This paper provides an insight for retailers, wholesalers, manufacturers’ green cosmetic industry, policymakers, whole cosmetic industry, and other stakeholders.

Beyond the Moral Domain: The Normative Sense Among the Chinese

In this paper we report a study on how different types of normatively relevant transgressions are evaluated by Chinese participants. We hypothesized that, given the continuing influences of Confucian worldview on contemporary Chinese societies, the Chinese will not make a distinction between moral (daode) and conventional norms of cultured behavior (wenming). Our results indicate that Chinese participants expressed a strong normative conviction not only towards harmful and unfair actions, usually subsumed under the moral domain in Western literature, but also towards violations of what would be widely accepted as conventional (or cultural) norms. Similarly, Chinese participants expressed a strong normative conviction towards violations of the traditional Chinese value of family reverence (xiao), thus further supporting our general thesis. Moreover, results indicate that, overall, explicit consi­derations of wenming (unculturedness) emerged as the best predictor of a normative conviction response among the Chinese. Though considerations of harm and fairness also emerged as significant predictors of normative conviction response. The results are discussed in the light of recent debates about the moral/conventional distinction and the scope of morality.

Utility- and Fairness-Based Spectrum Allocation of Cellular Networks by an Adaptive Particle Swarm Optimization Algorithm

In wireless and mobile communication, wireless spectrum is a limited and scarce resource. Properly allocating spectrum resource to different users is an important goal to meet the communication needs of people. The spectrum allocation problem in cellular network scenarios is studied in this paper. The network utility performance is assessed by two forms. One is no fairness consideration for linked users in the network, and the other is considering fairness for linked users. The spectrum allocation problem is represented as a maximization optimization problem. To solve the utility- and fairness-based spectrum allocation optimization, an adaptive particle swarm optimization is proposed based on sawtooth wave propagation technique (SAPSO). The SAPSO algorithm adapts all parameters in a sawtooth manner to accelerate convergence process. Simulation results show that the SAPSO algorithm is more efficient to solve spectrum allocation problem than the compared algorithms. Moreover, the results show that utilization with fairness among all linked users is a more suitable measure to improve quality of service for cellular networks.

Uterine Transplantation in Male to Female Transgender Women; A Cross-Sectional Survey Assessing Perceptions, Acceptability and Demand

Background: Uterine transplantation (UTx) has been demonstrated to be a viable fertility restoring treatment for women assigned female at birth with absolute uterine factor infertility. Recent advancements, as well as considerations of fairness and equality in reproductive care, have led to the possibility of UTx being undertaken in male to female (M2F) transgender women. Methods: This cross-sectional study utilised an electronic questionnaire to investigate the reproductive aspirations of M2F transgender women, including their perceptions of and motivations toward UTx. Findings: 182 M2F transgender women completed the questionnaire. The vast majority did not have children prior to transitioning (n=167; 92%) and expressed desire to have children in the future (n=171; 95%). The majority ‘agreed’ or ‘strongly agreed’ that the ability to gestate and give birth to their own children (n=171; 94%) and menstruate (n=161; 90%) would enhance perceptions of their femininity. Similarly, high proportions strongly agreed / agreed that having a transplanted, functioning vagina would improve their sex life (n=163; 90%), quality of life (n=163; 90%), and also help them to feel like ‘more of a woman’ (n=168; 93%). Nearly all respondents (n=180; 99%) believed that UTx would lead to greater happiness in M2F transgender women. More than three quarters (n=140; 77%) ‘strongly agreed’ or ‘agreed’ that they would be more inclined to cryopreserve sperm if UTx became a realistic option. Interpretation: This study provides novel insights into the reproductive aspirations of M2F transgender women and demonstrates multifaceted motivation to undergo UTx. There is clear desire to experience physiological experiences unique to women, such as menstruation and gestation, as well as potentially having a physiologically functioning transplanted vagina. It is foreseen that UTx, if proven feasible and safe in this setting, would facilitate the achievement of reproductive aspirations, improve quality of life and further alleviate dysphoric symptoms in M2F transgender women. Funding Statement: NWs research is funded by a Leverhulme Early Career Research Fellowship: Grant no: ECF-2018-113. SWs research is funded by a Wellcome Trust Senior Investigator Award. Grant no: 097897/Z/11/Z. Declaration of Interests: None of the co-authors have any competing interests. Ethics Approval Statement: Ethical approval to undertake the study was received from Imperial College London on 13th November 2018 (ICREC reference: 18IC4839).

Moral judgment modulates fairness consideration in the early outcome evaluation stage

Morality, concern for the welfare of others, is an important criterion of how individuals treat others, including justice, fairness, and rights. Moral judgment is the process of evaluating the behavior of others and oneself according to social norms. Morality might affect social cooperation with others by entailing the belief that someone should be rewarded or punished. The ultimatum game is a classic paradigm that can be used to study the fairness behavior of social cooperation. Previous studies have shown that some social factors (e.g., social distance, social exclusion, and social evaluation) influence fairness behavior in the ultimatum game. Using the event-related potential (ERP) technique to examine the neural basis of the ultimatum game, studies found that feedback-related negativity (FRN) was modulated by social factors. This effect indicates that the influence of social factors mainly appears in the early stage of outcome evaluation. However, the influence of moral judgment on social cooperation and its neural mechanism remains unclear. The present study focused on whether moral judgment would affect fairness consideration in the early outcome evaluation stage. For this purpose, we used moral sentences within the ultimatum game to assess the influence of moral judgment and fairness of offers on decision-making. A total of 25 participants who acted as respondents completed the ultimatum game with blood donors, murderers, and unidentified individuals as proposers. A moral sentence (e.g., He is a blood donor) was given as a reminder of the moral identity of the players before each round. Participants were told that other players would gain ￥50, and proposers would make an allocation offer. There were five types of allocation offers: ￥5, ￥10, ￥15, ￥20 or ￥25. Participants were asked to accept or reject the offers. At the same time, the ERP was locked to the onset of the offers. The acceptance rate of each offer was included in the behavioral data. The dependent variable was the acceptance rate of the five allocation offers and moral primes were the independent variable when performing one-way ANOVAs. Regarding ERP data, ￥5 and ￥10 were considered as unfair offers and ￥20 and ￥25 as fair offers in order to analyze the amplitudes of FRN and P300. Two-way repeated measures ANOVAs (moral judgment, three levels; offer fairness, two levels) were performed to compare ERP data. Behavioral results showed that the acceptance rate of unfair offers from blood donors was significantly higher than that of murderers. Furthermore, the acceptance rate of fair offers from murderers was significantly lower than that of blood donors and unidentified individuals. ERP results revealed that the FRN amplitude was more negative-going in response to unfair than to fair offers. The fairness of offers modulated FRN amplitude only regarding blood donors, but not for murderers and unidentified individual conditions. P300 was larger for fair offers compared to unfair offers and was not affected by moral judgment. These results indicate that when moral judgment conflicts with the fairness criterion, individuals might rely on moral judgment to make decisions. People may have a higher expectation of fairness from individuals with high moral standards, while unfair behaviors could induce strong negative emotions. FRN represents unfair behaviors that violate social norms and shows that the early outcome evaluation stage is also modulated by moral judgment, while the late stage is independent of moral judgment.

Fair regression for health care spending.

The distribution of health care payments to insurance plans has substantial consequences for social policy. Risk adjustment formulas predict spending in health insurance markets in order to provide fair benefits and health care coverage for all enrollees, regardless of their health status. Unfortunately, current risk adjustment formulas are known to underpredict spending for specific groups of enrollees leading to undercompensated payments to health insurers. This incentivizes insurers to design their plans such that individuals in undercompensated groups will be less likely to enroll, impacting access to health care for these groups. To improve risk adjustment formulas for undercompensated groups, we expand on concepts from the statistics, computer science, and health economics literature to develop new fair regression methods for continuous outcomes by building fairness considerations directly into the objective function. We additionally propose a novel measure of fairness while asserting that a suite of metrics is necessary in order to evaluate risk adjustment formulas more fully. Our data application using the IBM MarketScan Research Databases and simulation studies demonstrates that these new fair regression methods may lead to massive improvements in group fairness (eg, 98%) with only small reductions in overall fit (eg, 4%).

Beyond autonomy: repositioning the right to self-representation within the value of fair trial in criminal proceedings in Ghana

This article examines the legal framework for the grant and exercise of the right to self-representation in criminal proceedings in Ghana, using a doctrinal research approach. It finds that the exaltation of the value of autonomy of the right above considerations of procedural equality and trial fairness affects the integrity of the trial process. More importantly, the legal system in Ghana provides little or no standards setting the modalities of the exercise or revocation of the right. This article recommends a departure from the general standard of proceeding pro se which pays no regard to the competency of the accused person in favour of an adoption of a competency-based approach in order to guarantee an effective exercise of the right to self-representation. It also suggests the formulation and adoption of efficient standards in line with international law for the purpose of delimiting the scope of revocation of the right in criminal proceedings.

Understanding Tax Policy: How Do People Reason?

I study how people understand, reason, and learn about tax policy. The goal is to uncover the mental models that people use to think about income and estate taxes. To that end, I run large-scale online surveys and experiments on representative U.S. samples to elicit not only respondents' factual knowledge about tax policy and the income or wealth distributions, but also their understanding of the mechanisms of tax policy and their reasoning about it. The detailed survey questions are designed to address the three main factors emphasized in our core tax model that can shape support for or opposition to taxes: efficiency effects, distributional implications, and fairness considerations. But they also elicit broader concerns that could influence policy views, such as misperceptions, views of government, perceived spillovers from taxes, and views on how tax revenues are or should be spent. I decompose policy views into the various underlying factors and find that support for tax policy is most strongly correlated with views on the benefits of redistribution and fairness, as well as with views of the government. concerns play a more minor role. These correlational patterns are confirmed by the experimental approach, which shows people instructional videos that explain the workings and consequences of one of the aspects of tax policy (the and the Efficiency treatments) or that bring the two together and focus on the trade-off (the treatment). The Redistribution treatment and Economist treatments significantly increase support for more progressive taxes. I also find that there are partisan divergences not just in the final policy views, but also at every step of the reasoning about the underlying mechanisms of taxes, and most starkly on the fairness considerations. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Throughput Maximization by Time Switching in Multipoint WBAN With Fairness Consideration

In this paper, the average throughput maximization challenge with resources fairness consideration is proposed. In a multipoint wireless body area network (MP-WBAN), the time switching (TS) strategy and fairness algorithm are studied to improve system resources allocation performance. Under extreme circumstances, the sensors transfer command signals to the access point (AP) requesting the radio frequency (RF) energy from the source node. On the other hand, the sensors attached to the body surface transmit the perceived physiological information to the AP node. Owing to distance-dependent signal attenuation, the sensors near the AP node harvest more RF energy and time slots to achieve higher throughput. On the contrary, the sensors farther from the source node receive fewer RF energy and time slots to obtain lower throughput. Therefore, we design the common throughput maximization algorithm to allocate more time to farther sensors. At last, the effectiveness and accuracy of the studied fairness scheme are verified by simulation experimental data.

LED Half-Power Angle Optimization for Ultra-Dense Indoor Visible Light Communication Network Deployment

Due to limited interference range, the advantage of visible light communication (VLC) over wireless fidelity (WiFi) lies more in the unit-area transmission rate rather than the single-link transmission rate. To characterize the achievable transmission rate per unit area, we consider an indoor downlink VLC network with dense attocell configuration for the transmitters with single-color light-emitting diode (LED) and multi-color LEDs, assuming binomial distributed users. We divide each attocell into central region and boundary region, and propose the transmission protocols based on such attocell division. We optimize the LED half-power angle to maximize the mean achievable transmission rate per unit area. More specifically, we investigate the rates of cell-center and cell-boundary users under fairness consideration for the single LED transmitter system. We characterize the mean achievable transmission rate per unit area under the white light constraints in the multiple LEDs transmitter system. The performance of the proposed transmission protocols is evaluated by numerical results.

A Dynamic Shelter Location and Victim Resettlement Model Considering Equitable Waiting Costs

Catastrophic natural disasters cause devastating damage and leave a huge number of homeless people. Waiting for resettlement in a post-disaster environment brings human suffering, which is defined by waiting cost in this paper. Taking into account waiting cost and fairness consideration simultaneously, a mixed integer linear programming model is constructed for the multiperiod location-allocation process. Two fairness indicators are incorporated to guarantee both the whole-process equity and the periodic equity. The model is implemented in the General Algebraic Modeling System (GAMS) and solved by the CPLEX solver. An illustrative example is provided to explain the model characteristics. Furthermore, a case study of the Yushu earthquake is conducted to demonstrate the applicability of the model to practical problems.

Bias and Fairness in Machine Learning

This look at delves into the crucial area of Bias and Fairness in Machine Learning, aiming to scrutinize methodologies for the identification and relief of biases within algorithms, with a vital consciousness on making sure equitable results. As gadget studying applications grow to be an increasing number of pervasive in decision-making processes throughout numerous sectors, the need to address and rectify biases inside algorithms is paramount for fostering equity and mitigating accidental consequences. The research concentrates on exploring approaches to locate biases embedded in system getting to know fashions, acknowledging that biases can rise up from historic data, unsuitable version design, or inadvertent algorithmic decisions. The identity manner entails growing strong strategies to evaluate and quantify biases, making sure a comprehensive knowledge of the elements influencing algorithmic effects. By spotting and characterizing biases, the look at pursuits to contribute to a extra nuanced comprehension of the ethical implications related to algorithmic selection-making. Furthermore, the research investigates strategies to mitigate biases as soon as diagnosed. This includes refining algorithms and adjusting model parameters to rectify imbalances, with the final intention of selling fair and impartial predictions. The study recognizes that addressing bias is an iterative technique, requiring ongoing refinement to maintain pace with evolving statistics dynamics and societal modifications. A vital thing of this studies is the exploration of fairness-improving mechanisms within device learning frameworks. This consists of growing algorithms that explicitly account for fairness considerations, ensuring that the effect of selections is equitable throughout diverse demographic businesses. The take a look at scrutinizes one-of-a-kind fairness metrics and explores their software to evaluate and decorate algorithmic equity. By losing light on bias detection, mitigation strategies, and equity concerns, this research contributes to the continuing communicate surrounding the accountable deployment of gadget learning technologies. The outcomes of this study maintain implications for policymakers, builders, and stakeholders, emphasizing the significance of embedding fairness concepts in the material of device getting to know structures to promote just and equitable outcomes in numerous real-global packages.

Demonetization and Poor Economics: Warning signs that the government overlooked

Demonetization as a tool to curb black money in the Indian economy and promote a cashless society miserably measurable failed in the aspect of social welfare and poor economics or how the economics of being poor worked. This research paper shows that the government overlooked warning signs in the form of existing available data that with fair consideration would make demonetization infeasible because of the impact on poor people particularly in rural areas.