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近几年来语言测试公平性问题吸引了越来越多测试专家的关注。值得注意的是,当人们谈到语言测试公平性问题的时候,首先想到的就是公平性的定义,以及如何进行公平性的检验。然而,对公平性研究进行回顾是更好地了解公平性定义以及更好地制定出适用于公平性检验的指导性原则的前提。通过相关文献的查阅,文章总结出了迄今为止公平性问题研究所经历的三个阶段,并对语言测试公平性的相关问题进行思考与展望。 相似文献
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《Information processing & management》2023,60(1):103115
Fairness is fundamental to all information access systems, including recommender systems. However, the landscape of fairness definition and measurement is quite scattered with many competing definitions that are partial and often incompatible. There is much work focusing on specific – and different – notions of fairness and there exist dozens of metrics of fairness in the literature, many of them redundant and most of them incompatible. In contrast, to our knowledge, there is no formal framework that covers all possible variants of fairness and allows developers to choose the most appropriate variant depending on the particular scenario. In this paper, we aim to define a general, flexible, and parameterizable framework that covers a whole range of fairness evaluation possibilities. Instead of modeling the metrics based on an abstract definition of fairness, the distinctive feature of this study compared to the current state of the art is that we start from the metrics applied in the literature to obtain a unified model by generalization. The framework is grounded on a general work hypothesis: interpreting the space of users and items as a probabilistic sample space, two fundamental measures in information theory (Kullback–Leibler Divergence and Mutual Information) can capture the majority of possible scenarios for measuring fairness on recommender system outputs. In addition, earlier research on fairness in recommender systems could be viewed as single-sided, trying to optimize some form of equity across either user groups or provider/procurer groups, without considering the user/item space in conjunction, thereby overlooking/disregarding the interplay between user and item groups. Instead, our framework includes the notion of statistical independence between user and item groups. We finally validate our approach experimentally on both synthetic and real data according to a wide range of state-of-the-art recommendation algorithms and real-world data sets, showing that with our framework we can measure fairness in a general, uniform, and meaningful way. 相似文献
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将关系公平性概念引入到企业间合作关系的研究中,通过设计量表收集一手数据,使用因子分析和结构方程模型验证了关系公平性的构成维度,并分析了关系公平性对合作绩效的影响。研究发现:关系公平性包含分配公平性、程序公平性和互动公平性等3个维度。其中,分配公平性和程序公平性对企业间合作绩效具有显著的正向影响,而互动公平性因子对合作绩效没有实质性的影响。 相似文献
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《Information processing & management》2020,57(1):102138
With the increasing popularity and social influence of search engines in IR, various studies have raised concerns on the presence of bias in search engines and the social responsibilities of IR systems. As an essential component of search engine, ranking is a crucial mechanism in presenting the search results or recommending items in a fair fashion. In this article, we focus on the top-k diversity fairness ranking in terms of statistical parity fairness and disparate impact fairness. The former fairness definition provides a balanced overview of search results where the number of documents from different groups are equal; The latter enables a realistic overview where the proportion of documents from different groups reflect the overall proportion. Using 100 queries and top 100 results per query from Google as the data, we first demonstrate how topical diversity bias is present in the top web search results. Then, with our proposed entropy-based metrics for measuring the degree of bias, we reveal that the top search results are unbalanced and disproportionate to their overall diversity distribution. We explore several fairness ranking strategies to investigate the relationship between fairness, diversity, novelty and relevance. Our experimental results show that using a variant of fair ε-greedy strategy, we could bring more fairness and enhance diversity in search results without a cost of relevance. In fact, we can improve the relevance and diversity by introducing the diversity fairness. Additional experiments with TREC datasets containing 50 queries demonstrate the robustness of our proposed strategies and our findings on the impact of fairness. We present a series of correlation analysis on the amount of fairness and diversity, showing that statistical parity fairness highly correlates with diversity while disparate impact fairness does not. This provides clear and tangible implications for future works where one would want to balance fairness, diversity and relevance in search results. 相似文献
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我国R&D公平与效率的马太效应比较及协调发展 《科学学研究》2017,35(12):1832-1840
文章使用2002-2014年我国30个省市的面板数据,首先利用超效率DEA模型测算出各地区的R&D效率,并以R&D经费投入强度和政府R&D投入作为量化区域R&D公平的指标,随后构建Markov链模型将我国区域R&D公平与效率纳入统一分析框架,比较其马太效应大小,并构建二者协调发展的实施路径。研究结果表明,R&D公平的马太效应程度更加明显,那些享有高额R&D资金的地区始终获取充足的资助金额,而大部分地区却一直陷入R&D资金不足的窘迫局面,因此R&D公平问题更应该优先调节。本文认为政府应重点关注那些低投入高效率的省份,加大其R&D投入力度,既可以调节R&D公平的马太效应问题,又可保持我国区域R&D公平与效率的协调发展。 相似文献
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《Information processing & management》2023,60(2):103175
Task assignment, the core problem of Spatial Crowdsourcing (SC), is often modeled as an optimization problem with multiple constraints, and the quality and efficiency of its solution determines how well the SC system works. Fairness is a critical aspect of task assignment that affects worker participation and satisfaction. Although the existing studies on SC have noticed the fairness problem, they mainly focus on fairness at the individual level rather than at the group level. However, differences among groups in certain attributes (e.g. race, gender, age) can easily lead to discrimination in task assignment, which triggers ethical issues and even deteriorates the quality of the SC system. Therefore, we study the problem of task assignment with group fairness for SC. According to the principle of fair budget allocation, we define a well-designed constraint that can be considered in the task assignment problem of SC systems, resulting in assignment with group fairness. We mainly consider the task assignment problem in a common One-to-One SC system (O2-SC), and our goal is to maximize the quality of the task assignment while satisfying group fairness and other constraints such as budget and spatial constraints. Specifically, we first give the formal definition of task assignment with group fairness constraint for O2-SC. Then, we prove that it is essentially an NP-hard combinatorial optimization problem. Next, we provide a novel fast algorithm with theoretical guarantees to solve it. Finally, we conduct extensive experiments using both synthetic and real datasets. The experimental results show that the proposed constraint can significantly improve the group fairness level of algorithms, even for a completely random algorithm. The results also show that our algorithm can efficiently and effectively complete the task assignment of SC systems while ensuring group fairness. 相似文献
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基于高科技中小风险企业的样本数据,经验性地分析揭示了公平性偏好经济效应的微观路径机理,为我国企业在公平性环境下加强知识资本开发并促进企业的持续成长提供了现实性的理论借鉴。研究结果表明:公平性偏好的经济效应在我国企业运营中日渐显著,特别是与知识资本开发存在着内在的一致性;限于战略导向的缺失与实施经验的匮乏,公平性管理策略的运用有待扩展与深入。 相似文献
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本文提出多用户多中继环境下基于用户公平性的最优中继选择算法及低复杂度次优中继选择算法。算法利用跨层信息,最大化系统信息速率并保证各用户信息速率的比例公平性。次优算法在保证系统性能的前提下,降低算法复杂度。仿真结果表明,相较于盲选择算法,该文所提出的算法有效提高系统性能及用户公平性。 相似文献
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社会公平是人类永恒的追求,也是贯穿于当代中国社会治理的核心价值理念。然而当前社会存在严重的阶层差异与阶层固化现象,已在很大程度上制约了社会公平的实现。对此,社会阶层心理学从社会客观现实、民众主观感受和心理干预策略几个方面出发,围绕着社会分层阻碍社会公平的心理机制、不同阶层感知社会分层与公平的心理特点以及如何增强阶层流动进而更好地促进社会公平这几个核心问题展开了研究。未来心理学视角下的社会分层与社会公平研究应更加完善本土化的理论,运用多样化的研究方法,并且进一步推进研究成果的应用,为社会治理实践服务。 相似文献
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薪酬满意度对科技人员的工作积极性和科研绩效有着重要影响,并进而影响到创新型国家的建设。公平是影响薪酬满意度的重要因素。本文在文献回顾的基础上,将科技人员薪酬满意感分解为工资收入满意感、保障福利满意感和组织成就满意感三个方面,并将公平感分解为比较公平感和制度公平感两方面,然后采用结构方程模型方法对江苏省13地市大样本（共发放问卷15800份）调研数据进行了实证研究,验证了公平感是科技人员薪酬满意感的重要影响因素假设,而且发现工资收入满意感和保障福利满意感受比较公平感的影响较大,制度公平感对组织成就满意感影响较大。在结论分析中提出了相应的政策建议。 相似文献
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构建了一个由合作社与核心企业组成的二级生鲜农产品供应链,考虑合作社与核心企业具有公平心理,研究在完全理性与公平心理下的合作社质量投入以及核心企业批发价格定价决策.结果发现:合作社公平偏好行为有助于提升核心企业的定价水平以及自身的质量投入水平,但在核心企业具有公平关切时,合作社公平偏好对其存在抑制作用;同时,核心企业订货量在不同的公平心理下对定价与质量投入也存在不同的影响.在多种公平偏好影响下,供应链盟员对于利润以及公平效用的追逐程度不同将影响盟员利润、效用以及产品的质量水平. 相似文献
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本文通过建立中介模型,实证分析了联盟企业间关系公平性对关系承诺的影响,并探讨了企业间信任的中介作用。论文以江苏230家企业为研究样本,通过量表收集数据,并使用层级回归分析的方法来检验所提出的假设。研究结果表明,我国企业间合作关系中存在着关系公平性对关系承诺的影响路径。其中,分配公平性直接促进企业间情感承诺水平的提升,同时通过才能信任对情感承诺产生间接影响;程序公平性主要通过才能信任这一中介变量对情感承诺实施正向影响;互动公平性可以降低企业间的计算承诺水平,同时还有助于提升企业间的仁善信任水平,间接对计算承诺产生影响。本文最后提出了相应的管理建议。 相似文献
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在构建社会主义和谐社会的过程中,公平正义具有鲜明的时代内涵和特色。正确把握公平正义的内涵,有助于我们深刻地认识到公平正义原则作为和谐社会的核心价值理念的重要性。同时,为了实现社会安定有序和公平正义,必须通过一系列措施和途径,不断加强改革和发展。 相似文献
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同行评议公正性的影响因素分析 总被引：15，自引：2，他引：15
同行评议是科学评价的重要方式,也是政府基础科学资助机构资源配置的主要方式之一,公正高效的同行评议是保证科学质量的基础。本文将通过区分影响同行评议公正性的两种类型三个方面的因素,即评议过程本身的因素和评议过程以外的因素,以及评议过程中的制度性因素和非制度性个人因素,较为系统地分析影响公正性诸因素,以为制定公正性政策提供依据。 相似文献
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中美同行评议公正性政策比较研究 总被引：6，自引：0，他引：6
同行评议是科学评价的重要方式,也是政府基础科学资助机构资源配置的主要方式之一,公正高效的同行评议是保证科学质量的基础。本文通过比较美国国家科学基金会(NSF)与中国国家自然科学基金委员会(NSFC)的同行评议公正性政策,分析其政策实施的背景和制度条件,进而提出改进NSFC评议公正性的建议。 相似文献
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综合考虑横纵向公平关切对知识共享的影响，探讨各类因素影响下供应链企业知识共享决策及其行动演化路径，为供应链企业间的知识共享决策提供理论参考。首先，分析供应链企业知识共享行为的影响因素；其次，基于演化博弈理论构建纵向和横向公平关切下的知识共享演化博弈模型，并分析其演化稳定策略；最后，基于MATLAB数值仿真分析各因素影响下企业共享策略的演化路径。结果发现：适当水平的知识共享量、恰当的收益分配对企业的知识共享行为有促进作用；在纵向公平关切下，企业更关心协同收益的分配比例，收入差距对企业决策的影响可忽略不计，而横向公平关切从短期看可能促进企业知识共享行为的发生，但从长期来看不利于企业间的知识共享。 相似文献
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教室作为学校教育的主阵地,教室中的公平与否影响着教育公平的实现。中小学教室中的公平主要存在两大问题：1）教室里教师客观的教育行为不公平,包括提问的不平等,互动的不公平,评价体制的不科学,教室资源分配的不合理。2）教室里学生产生不公平的情绪体验,包括师生关系的不和谐,基于性别、阶层的歧视等。中小学如何跨越从教室不公平到教室公平最后的0.5米？本文针对性地提出了包括分层提问,因材施问;建立科学的教室评价体制;合理分配教室资源,构建和谐的师生关系;提高教师素质,加强师德建设等消除教室不公平的措施。 相似文献