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PurposeMost of the past studies related to organisational justice focussed on different types of justice, such as procedural justice, distributive justice and interactional justice either separately or collectively. Still, further investigation on the overall concept of fairness is required to extend theoretical generalisability. Moreover, researchers argued that overall fairness rather than a specific type represents more concrete situation about employees' perception of fairness within an organisation. Considering this, the purpose of this paper is to examine the mediating effect of overall fairness perception (OFP) in relation to workplace outcome as well as its predictive ability on employees' attitude and behaviour in term of psychological ownership and citizenship behaviour.Design/methodology/approachA total of 250 questionnaires were distributed among the employees of financial institutions in Malaysia, which yielded 150 completed usable responses. Smart PLS (version 3) software and SPSS were utilised in order to analyse the data.FindingsThe results revealed that overall fairness plays a crucial role as a mediator as well as a predictor. Limitations and future research directions are also discussed.Practical implicationsThis study provides useful insights for the mangers of financial institutions. It also suggests strategies about how to manage justice and workplace outcomes at workplace.Originality/valueThis paper is among the pioneers to address the mediating role of OFP in relations to workplace attitude and behaviour in non-western context.

Abstract
This article focuses on a specific standard by which the right to a fair trial is interpreted in the context of the right to legal assistance and the right to examine witnesses under Article 6 ECHR, the standard of overall fairness. The first section argues that the standard of overall fairness undermines the rule of law and represents a problematic conception of the right to a fair trial. The second section links overall fairness to the Court's wider methodological approach to adjudication, namely ad hoc balancing, and establishes that ad hoc balancing is vulnerable to similar critiques. The third section advocates for a legal doctrine which rejects the theoretical assumptions of balancing and sets the basis for a reconceptualisation of the European Court of Human Rights' approach to methodology and to the grant of remedies.

This paper examines the preferences for income tax progressivity, other tax fairness issues, and tax compliance of a national sample of nearly six hundred heads of U.S. households. The results reveal that mean public preferences for fair tax burdens are close to actual effective tax rates; however, the similarity between average preferred and actual effective tax rates masks an underlying schism between three groups: (I) those who believe tax rates should be higher for upper income persons (steep progressives), (2) those who prefer mildly progressive tax rates (mild progressives), and (3) those who believe tax rates should be flat ("flatraters). The analysis includes demographic and fairness profiles associated with tax rate preferences. Attitudes about the overall fairness of the income tax, exchange equity with the federal government, government spending, tax complexity, and tax compliance behavior are examined. In general, respondents' stated preferences for vertical equity approximate the current distribution of the income tax burden, yet there is a relatively high consensus that the income tax is unfair, especially with regard to the ability of wealthy taxpayers to exploit loopholes to avoid paying their fair share, and that respondents regard their own tax burdens as unfair. These results suggest that providing information to the public about the relative amount of income taxes paid by upper income individuals and the effects of recent limitations on "loopholes" could improve public attitudes about the fairness of the income tax and tax compliance.

PurposeDrawing on the ability-motivation-opportunity model, this study investigates how gender-inclusive human resource management practices and overall fairness perception promote the career progression of female employees via psychological empowerment.Design/methodology/approachPartial least structural equation modelling (PLS-SEM) was applied to two-waves data collected from 308 respondents from Pakistan to confirm hypotheses.FindingsFindings suggest that gender-inclusive HRM practices substantially affect female employees' psychological empowerment and career progression. Psychological empowerment is a mediating mechanism that explains the effect of gender-inclusive HRM practices on female employees' career progression. Finally, overall fairness perception further amplifies the effect of gender-inclusive HRM practices on psychological empowerment and career progression.Practical implicationsThe study provides evidence to policymakers that organizations may promote psychological empowerment and career progression of female employees by implementing gender-inclusive HRM practices and promoting overall fairness perception.Originality/valueThis study contributes to achieving the SDGs by examining the impact of gender-inclusive HRM practices and overall fairness perception on female employees' psychological empowerment and career progression. Specifically, it aligns with "Goal 5 - achieve gender equality and empower all women and girls" and "Goal 8 - promote sustained, inclusive, and sustainable economic growth, full and productive employment, and decent work for all".

Siting controversies have become familiar in windpower development. Process and outcome fairness in the form of economic benefits to local communities and inclusion in decision-making processes are recognised as important elements in local acceptance of windpower installations. To these, we add the concept of "relative fairness" influencing perceptions of overall fairness. In this article, we examine why Norwegian municipalities agree to host windpower, and the role of process, outcome and relative fairness in this decision. Municipalities are central in providing welfare services, and in ensuring a viable local economy and local workplaces. Process fairness is important, as is evident when municipalities have little influence in the detailed planning of the plants. Also, outcome fairness, in the form of economic compensation – particularly through property tax – is decisive for positive attitudes towards windfarms, as municipalities can strengthen their role as welfare providers and boost local economic activities. Less emphasised are the effects on global climate and national climate goals. However, effects on local landscape and nature are also important for municipalities, as became clear when the national government proposed withdrawing the municipalities' possibilities of levying property taxes. The municipalities argue that it is only fair to receive something in return for hosting windmills, and relative fairness is important to their argument for equal treatment regarding hydro- and wind-power electricity production in the form of a natural resource tax. ; publishedVersion

AbstractThe use of machine learning as an input into decision-making is on the rise, owing to its ability to uncover hidden patterns in large data and improve prediction accuracy. Questions have been raised, however, about the potential distributional impacts of these technologies, with one concern being that they may perpetuate or even amplify human biases from the past. Exploiting detailed credit file data for 800,000 UK borrowers, we simulate a switch from a traditional (logit) credit scoring model to ensemble machine-learning methods. We confirm that machine-learning models are more accurate overall. We also find that they do as well as the simpler traditional model on relevant fairness criteria, where these criteria pertain to overall accuracy and error rates for population subgroups defined along protected or sensitive lines (gender, race, health status, and deprivation). We do observe some differences in the way credit-scoring models perform for different subgroups, but these manifest under a traditional modelling approach and switching to machine learning neither exacerbates nor eliminates these issues. The paper discusses some of the mechanical and data factors that may contribute to statistical fairness issues in the context of credit scoring.

Research suggests that fairness perceptions matter to people who are asked to evaluate the acceptability of risks or risk management. Two separate national random surveys (n = 305 and n = 529) addressed Americans' concerns about and acceptance of nanotechnology risk management in the context of the degree to which they view scientists and risk managers as fair. The first survey investigated general views about scientists across four proposed dimensions of fairness (distributional, procedural, interpersonal, and informational). The results show that respondents who believe that the outcomes of scientific research tend to result in unequal benefits (distributional fairness) and that the procedures meant to protect the public from scientific research are biased (procedural fairness) were more concerned about nanotechnology. Believing scientists would treat them with respect (interpersonal fairness) and ensure access to information (informational fairness) were not significant predictors of concern. The second study also looked at these four dimensions of fairness but focused on perceptions of risk managers working for government, universities, and major companies. In addition to concern, it also examined acceptance of nanotechnology risk management. Study 2 results were similar to those of study 1 for concern; however, only perceived informational fairness consistently predicted acceptance of nanotechnology risk management. Overall, the study points to the value of considering fairness perceptions in the study of public perceptions of nanotechnology.

Globalization, migration, initiatives for social justice, and other developments have made the representation of diverse groups and relations among them an important issue for organizations in many nations. In the United States, government agencies have increasingly invested in managing demographic diversity effectively. This study examines how perceived organizational fairness combined with diversity management relates to employees' job satisfaction in public organizations. To test these relationships we analyze data drawn from the 2006 Federal Human Capital Survey (FHCS) using hierarchical regressions—hierarchical ordered logistic regressions and hierarchical linear regressions. The results indicate that in an agency where members perceive higher levels of organizational fairness, and where employees perceive that diversity is more effectively managed, employees report higher satisfaction with their jobs. Interestingly, while high organizational fairness in association with diversity management efforts enhances the overall job satisfaction of employees, its positive impact was smaller for racial/ethnic minorities than Whites. In contrast, women tend to report higher job satisfaction than men when they perceive that their agency manages diversity effectively, and has just and fair procedures, whereas the relationship was not significant in the hierarchical linear regression model.

Balancing speed and quality during crises pose challenges for ensuring the value and utility of data in social science research. The COVID-19 pandemic in particular underscores the need for high-quality data and rapid dissemination. Given the importance of behavioural measures and compliance with measures to contain the pandemic, social science research has played a key role in policymaking during this global crisis. This study addresses two key research questions: How FAIR (findable, accessible, interoperable and reusable) are social science data on the COVID-19 pandemic? Which study features are related to the level of FAIRness scores of datasets? We assess the FAIRness of n = 1131 articles, retrieved through a keyword search in the Web of Science database, employing both automated and manual coding methods. Our study inclusion criteria encompass empirical studies on the COVID-19 pandemic published between 2019 and 2023 with a social science focus and explicit reference to the underlying dataset(s). Our analysis of n = 45 datasets reveals substantial differences in FAIRness for different types of research on the COVID-19 pandemic. The overall FAIRness of data is acceptable, although particularly Reusability scores fall short, in both the manual and the automatic assessment. Further, articles explicitly linked to the Social Science concept in the OpenAlex database exhibit a higher mean overall FAIRness value. Based on these results, we derive recommendations for balancing ethical obligations and the potential tradeoff between speed and data (sharing) quality in social-scientific crisis research.

"Fairness in the Workplace takes a multi-dimensional approach to the concept of organizational fairness, one that views organizational fairness as being comprised of procedural justice, organizational politics, organizational trust, and psychological contract breach, all of which are indicators of the global evaluation of the (un)fairness of the organization. This evaluation, in turn, predicts the employees' attitudes and behaviors. Such an approach moves from a simplified view of the focal constructs as unique perceptions to a more nuanced understanding of each construct as representing one aspect of the overall assessment of the organization as fair or unfair. By combining them into a concept that represents a higher level of abstraction, we can develop a robust scale with which to measure organizational (un)fairness that has the potential to improve our predictions about employees' attitudes and behaviors. This approach expands existing motivation theories. Furthermore, the book covers the relationship between organizational fairness and organizational outcomes. "--

This work complement the study made by previous researchers on destination image who investigated precisely the relationship between destination image, perceived value, and overall satisfaction. Made in Douala-Cameroon, the particularity of this work reside on the fact that there is an implication for the local people (residents of this city). The result of this research shows that destination image is positively linked to perceive value; destination image and overall satisfaction are positively linked; then perceive value plays the role of a mediator between destination image and overall satisfaction. Some implications were mention but the most critical ones were focus on the government, the private sectors, and the local residents in issues such as the protection of goods and services, trust, and fairness if Douala-Cameroon is to be one of the best destination to visit in Cameroon and why not in the entire Africa. Keywords: Destination image; Perceived value; Overall Satisfaction; Cameroon; Douala. ; ÖZ: Bu çalışma tam olarak algılanan değer, genel memnuniyet ve hedef görüntü arasındaki ilişki araştırıldı ayrıca görüntü üzerinde önceki araştırmacılar tarafından yapılan çalışmayı tamamlayacak. Kamerun da yapılan bu çalışma özelliği yerel halk için bir anlamı var, öyle ki (bu şehrin sakinleri) üzerinde bulunur. Bu araştırmanın sonucunda gösterir ki hedef görüntüsü olumlu şekilde bağlantılıdır algılanan değerle birlikte bu da olumlu olarak etkilidir genel memnuniyet değerleriyle. Douala-Kameron'un tüm Afrika'da değil, Kameron'daki en iyi ziyaret noktalarından biri olması için bazı sonuçlardan bahsedildi ama en kritik olanları devlete odaklananlardı; özel sektörler ve yerel halk, mallar ve hizmetlerin korunması, güven ve adalet konuları. Anahtar Kelimeler: Hedef Görüntü; Algılanan değer; Genel memnuniyet; Kamerun; Douala ; Master of Science in Tourism Management. Thesis (M.S.)--Eastern Mediterranean University, Faculty of Tourism, 2015. Supervisor: Assist. Prof. Dr. Rüçhan Kayaman.

This article examines Swedish asylum deliberations regarding families with children with severe apathy, a condition where the child gradually loses all bodily functions. The article outlines the political context and medical evidence that has evolved since the beginning of the 2000s. It uses case studies and frequencies drawing from a case-file inventory covering 24 families, many with minority belonging. The asylum process, case law and the decision makers' role in reiterating and interpreting the families' asylum narratives are explored, analysed and discussed using discourse analysis and interpreted using intersectional theory. Findings suggest that the asylum narratives are greatly reduced and reformulated in a way that seems detrimental to state obligations towards, for example, rape victims. Findings also suggest that political persecution should be taken more seriously by Swedish migration authorities. Finally, evidence indicates a need for a feminist perspective, and an overall strategy, at authority level that does not discriminate.

Teams of collaborators from Colombia, Mexico, Pakistan, and Thailand have adapted a policy tool originally developed for evaluating health insurance reforms in the United States into "benchmarks of fairness" for assessing health system reform in developing countries. We describe briefly the history of the benchmark approach, the tool itself, and the uses to which it may be put. Fairness is a wide term that includes exposure to risk factors, access to all forms of care, and to financing. It also includes efficiency of management and resource allocation, accountability, and patient and provider autonomy. The benchmarks standardize the criteria for fairness. Reforms are then evaluated by scoring according to the degree to which they improve the situation, i.e. on a scale of -5 to 5, with zero representing the status quo. The object is to promote discussion about fairness across the disciplinary divisions that keep policy analysts and the public from understanding how trade-offs between different effects of reforms can affect the overall fairness of the reform. The benchmarks can be used at both national and provincial or district levels, and we describe plans for such uses in the collaborating sites. A striking feature of the adaptation process is that there was wide agreement on this ethical framework among the collaborating sites despite their large historical, political and cultural differences.

Teams of collaborators from Colombia, Mexico, Pakistan, and Thailand have adapted a policy tool originally developed for evaluating health insurance reforms in the United States into "benchmarks of fairness" for assessing health system reform in developing countries. We describe briefly the history of the benchmark approach, the tool itself, and the uses to which it may be put. Fairness is a wide term that includes exposure to risk factors, access to all forms of care, and to financing. It also includes efficiency of management and resource allocation, accountability, and patient and provider autonomy. The benchmarks standardize the criteria for fairness. Reforms are then evaluated by scoring according to the degree to which they improve the situation, i.e. on a scale of -5 to 5, with zero representing the status quo. The object is to promote discussion about fairness across the disciplinary divisions that keep policy analysts and the public from understanding how trade-offs between different effects of reforms can affect the overall fairness of the reform. The benchmarks can be used at both national and provincial or district levels, and we describe plans for such uses in the collaborating sites. A striking feature of the adaptation process is that there was wide agreement on this ethical framework among the collaborating sites despite their large historical, political and cultural differences.