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11.
易培强 《广播电视大学学报》2013,(4):3-9
收入再分配的主旨要求其制度安排具有公平性。为了解决仍严重存在的保证收入再分配公平性的制度缺失问题,收入再分配制度建设要更加注重公平,包括：完善能有效调节收入差距的税收制度;进一步提高社会保障制度的统一性、普惠性、公平性;积极推进公共服务均等化;优化财政支出结构。深化收入再分配制度改革,要正确认识和处理更加注重公平与兼顾效率、坚持改革目标与逐步推进、政府主导与调动社会积极性等关系。 相似文献
12.
Alan K. Goodboy Rebecca M. Chory Katie Neary Dunleavy 《Communication Research Reports》2013,30(4):255-265
This study examined the relationships between perceptions of organizational justice and enacting organizational dissent. Participants were 107 full-time employees working in various organizations. Results indicated that employee perceptions of distributive and interpersonal justice negatively predicted latent dissent, while perceptions of informational justice positively predicted latent dissent. Perceptions of interpersonal justice were the strongest predictor of latent dissent. Perceptions of justice were not related to articulated or displaced dissent. Future research should continue to explore triggering agents of dissent in organizations. 相似文献
13.
Rachel Duffy Andrew Fearne Sue Hornibrook Karise Hutchinson Andrea Reid 《International Journal of Information Management》2013
Given the crucial role of suppliers in collaborative supply chains, it is surprising that little attention has been paid to the nature and management of supplier relationships in the implementation of a retailer's Customer Relationship Management (CRM) strategy. To address this gap in the extant literature, the theory of organizational justice is used to explore the extent to which perceived fairness in buyer–supplier relationships supports or inhibits supplier engagement with the CRM process. The rationale is that suppliers who feel fairly treated by key retail customers are more likely to invest resources in the acquisition and use of data central to the retailer's CRM strategy. By empirically testing a conceptual model linking downstream CRM to upstream SRM, the results provide evidence to indicate that customer data use is significantly influenced by perceptions of fairness, particularly with respect to the distribution of rewards, and the transparency of decision-making processes. As a key criticism of CRM centers upon the failure of organizations to exploit the full potential of customer data, the results highlight the usefulness of understanding the relational linkages between buyers and suppliers and the consequential behavior of suppliers in terms of engagement with customer data vital to the success of retailers’ CRM strategies. 相似文献
14.
由社会主义核心价值体系凝练出的社会主义核心价值观,是我国各行业核心价值观确立的依据。当前人们对社会主义核心价值观的提法尚未一致,但"人本"、"公正"、"和谐"是多数人的共识,因此可作为我国体育行业的核心价值观。"人本"、"公正"、"和谐"是一个整体,"人本"是体育发展的立足点,"公正"是"人本"价值实现的保证,而"人本"、"公正"所追求的就是体育的"和谐"发展和体育对促进社会和谐的贡献,三者相互联系、相辅相成而成为体育核心价值观,共同引领我国体育的健康发展。 相似文献
15.
异地高考改革从实质上讲是教育公平问题,涉及多方利益,改革是寻求各方利益的平衡点。异地高考改革有着深刻的社会背景,经济社会的发展和城市化进程是其产生的主要背景。时至今日,包括北京、上海、广州等几个呼声最高的地区和省份都出台了相关政策措施,但是仍未有实质性进展,进城务工人员随迁子女就地高考问题仍未得到彻底解决。异地高考方案迟迟未能突破,面临着一系列困境,本文概括为资格认定难、利益平衡难、改革独行难和实施操作难四个方面。 相似文献
16.
社会主义市场经济条件下持有、转让和矫正的公正贯穿于三次收入分配的过程中,是收入分配改革目标实现的三大维度。我国在收入分配改革的进程中要把握持有、转让、矫正的公正原则,通过推进权利平等、收益合法和尊重劳动保障持有的公正,完善税收、转移支付和社会保障制度推进转让的公正,倡导先进文化引导矫正的公正。 相似文献
17.
教育正义——我国教育发展的新追求 总被引：1，自引：0，他引：1
江义永 《贵州教育学院学报》2009,25(10):5-8
近年来,我国教育规模发展迅速,然而教育在高效发展的同时也带来了负面的问题,即教育正义性的问题。罗尔斯认为,正义是社会制度的首要价值,因而教育正义与否则是检验教育制度的首要价值标准。因此,教育的高效性与正义性之间的矛盾,教育正义怎样实现都是值得研究的课题。 相似文献
18.
协同学理论蕴含了丰富的系统和谐思想,对于局部与整体、宏观与微观、合作与竞争、组织与被组织、稳定与不稳定等关系及其和谐都给予了大量的富有启发性的论述。本文由此出发,探讨了构建社会主义和谐社会的又一理论基础。文章指出,在我国社会主义市场经济的大系统之内,无论其宏观的目标,还是其微观的目的;不论其各种经济主体、各种所有制形式,还是其经济、政治、思想文化等诸多领域,均会发生良性的互动。这些将引发生产力发展、共同富裕、人的全面发展等方面的协同;将引发经济、政治、思想文化等诸多领域的协同。这些协同正是构建社会主义和谐社会的内在根据。 相似文献
19.
《Information processing & management》2023,60(2):103226
Nowadays assuring that search and recommendation systems are fair and do not apply discrimination among any kind of population has become of paramount importance. This is also highlighted by some of the sustainable development goals proposed by the United Nations. Those systems typically rely on machine learning algorithms that solve the classification task. Although the problem of fairness has been widely addressed in binary classification, unfortunately, the fairness of multi-class classification problem needs to be further investigated lacking well-established solutions. For the aforementioned reasons, in this paper, we present the Debiaser for Multiple Variables (DEMV), an approach able to mitigate unbalanced groups bias (i.e., bias caused by an unequal distribution of instances in the population) in both binary and multi-class classification problems with multiple sensitive variables. The proposed method is compared, under several conditions, with a set of well-established baselines using different categories of classifiers. At first we conduct a specific study to understand which is the best generation strategies and their impact on DEMV’s ability to improve fairness. Then, we evaluate our method on a heterogeneous set of datasets and we show how it overcomes the established algorithms of the literature in the multi-class classification setting and in the binary classification setting when more than two sensitive variables are involved. Finally, based on the conducted experiments, we discuss strengths and weaknesses of our method and of the other baselines. 相似文献
20.
《Information processing & management》2023,60(2):103224
Artificial intelligence (AI) is rapidly becoming the pivotal solution to support critical judgments in many life-changing decisions. In fact, a biased AI tool can be particularly harmful since these systems can contribute to or demote people’s well-being. Consequently, government regulations are introducing specific rules to prohibit the use of sensitive features (e.g., gender, race, religion) in the algorithm’s decision-making process to avoid unfair outcomes. Unfortunately, such restrictions may not be sufficient to protect people from unfair decisions as algorithms can still behave in a discriminatory manner. Indeed, even when sensitive features are omitted (fairness through unawareness), they could be somehow related to other features, named proxy features. This study shows how to unveil whether a black-box model, complying with the regulations, is still biased or not. We propose an end-to-end bias detection approach exploiting a counterfactual reasoning module and an external classifier for sensitive features. In detail, the counterfactual analysis finds the minimum cost variations that grant a positive outcome, while the classifier detects non-linear patterns of non-sensitive features that proxy sensitive characteristics. The experimental evaluation reveals the proposed method’s efficacy in detecting classifiers that learn from proxy features. We also scrutinize the impact of state-of-the-art debiasing algorithms in alleviating the proxy feature problem. 相似文献