A Multi-Level Process Model for Understanding Diversity Practice Effectiveness

Key Findings: The issue of workforce diversity has been at the forefront of organizational concerns for many years. Not surprisingly, this topic has generated reams of research aimed at shedding light not only on the challenges involved, but also on ways these challenges have been and can be addressed. This paper reports on a comprehensive survey of the most recent studies in an effort to uncover what has been learned and what remains to be examined. While the paper is aimed primarily at researchers, it also offers a number of insights of relevance to managers and others who are responsible for designing and administering diversity-related initiatives in today’s organizations. Initially, the review focused on studies examining particular types of diversity- related policies and practices (affirmative action, targeted recruiting, training, work-life integration, mentoring, etc.) to ascertain what could be said about their general effectiveness. The results were disappointing. No activity was found to be consistently effective; some studies turned up positive relationships, but more often the results were mixed or inconclusive and occasionally even negative. If, as these findings suggest, organizations cannot rely on specific diversity- related activities to consistently produce favorable results, the logical question to ask is: “Why?” While the authors offer several reasons for this state of affairs, the overall theme that emerges relates to the absence of a holistic view of the situation. To wit: Organizations tend to focus too much on popular programs and too little on specific, desired outcome(s). When initiatives are undertaken with no clear goals in mind, it should not be surprising to find that quite often very little is accomplished. In too many cases diversity-related activities are studied (and implemented) in isolation and, thus, inadequate attention is given to how new procedures might interact with those already in place to affect outcomes. This is unfortunate, since HR strategy researchers have thoroughly documented the power of mutually-reinforcing “bundles” of activities in numerous studies across a wide variety of settings. Many factors come into play between the formal announcement of diversity- related initiatives, bundled or otherwise, and relevant organizational outcomes. To understand why initiatives do or do not work requires that these factors be carefully considered. Are espoused initiatives implemented as planned? Do implemented initiatives result in desired employee behaviors? Do the new employee behaviors produce positive organizational outcomes? And in each case, why or why not? Clearly studies that address all of these questions are difficult to do, but they must be done if we are to have any chance of acquiring the information and insights needed to make the most of current and future diversity-related initiatives. acquiring the information and insights and future diversity-related initiatives

The Diversity of Diversity: Implications of the Form and Process of Localised Urban Systems

This paper summarises research into localised urban systems which accounts for variations in styles of diversity within multi-cultural cities. New work builds on previous studies in London and Turin. The first produced an ideal type model of open:closed urban systems and evidence that the former have better capacity to incorporate incomers. The second revealed the need to adapt the model to account also for the process of diversity. This third phase combines ethnography with computer simulations to reveal emergent properties as well as present styles of urban systems, and to rank the variables driving change. The outcome will be a typology for users dealing with migrant settlement and urban regeneration.Typology of urban systems, Diversity, Relatedness, Process models, Ideal types

Inheritance-Based Diversity Measures for Explicit Convergence Control in Evolutionary Algorithms

Diversity is an important factor in evolutionary algorithms to prevent premature convergence towards a single local optimum. In order to maintain diversity throughout the process of evolution, various means exist in literature. We analyze approaches to diversity that (a) have an explicit and quantifiable influence on fitness at the individual level and (b) require no (or very little) additional domain knowledge such as domain-specific distance functions. We also introduce the concept of genealogical diversity in a broader study. We show that employing these approaches can help evolutionary algorithms for global optimization in many cases.Comment: GECCO '18: Genetic and Evolutionary Computation Conference, 2018, Kyoto, Japa

Building China: Informal Work and the New Precariat

[Excerpt] This book makes three main contributions to our understanding of informal work in China. First, it documents diversity in employment relations and the labor market. This diversity exists in spite of the fact that all of these workers are similar: they are all men who are unregistered migrants working informally in the construction industry in major cities in China. This book helps us make sense of that diversity and the diversity of informal precarious work more generally. Second, it expands our understanding of China’s emerging labor regime, which is central to labor control, intimately related to the urbanization process, and ultimately linked to China’s overall economic success. Finally, it shows how these migrants struggle against the disciplining process, contest exploitation, and protest in unique ways. Just as with other workers toiling under capitalism, important structural forces shape their work and lives but are not deterministic. Thus, this large, emerging segment of workers should not be overlooked when analyzing the complexities of class and class politics in China

Learning to Diversify Web Search Results with a Document Repulsion Model

Search diversification (also called diversity search), is an important approach to tackling the query ambiguity problem in information retrieval. It aims to diversify the search results that are originally ranked according to their probabilities of relevance to a given query, by re-ranking them to cover as many as possible different aspects (or subtopics) of the query. Most existing diversity search models heuristically balance the relevance ranking and the diversity ranking, yet lacking an efficient learning mechanism to reach an optimized parameter setting. To address this problem, we propose a learning-to-diversify approach which can directly optimize the search diversification performance (in term of any effectiveness metric). We first extend the ranking function of a widely used learning-to-rank framework, i.e., LambdaMART, so that the extended ranking function can correlate relevance and diversity indicators. Furthermore, we develop an effective learning algorithm, namely Document Repulsion Model (DRM), to train the ranking function based on a Document Repulsion Theory (DRT). DRT assumes that two result documents covering similar query aspects (i.e., subtopics) should be mutually repulsive, for the purpose of search diversification. Accordingly, the proposed DRM exerts a repulsion force between each pair of similar documents in the learning process, and includes the diversity effectiveness metric to be optimized as part of the loss function. Although there have been existing learning based diversity search methods, they often involve an iterative sequential selection process in the ranking process, which is computationally complex and time consuming for training, while our proposed learning strategy can largely reduce the time cost. Extensive experiments are conducted on the TREC diversity track data (2009, 2010 and 2011). The results demonstrate that our model significantly outperforms a number of baselines in terms of effectiveness and robustness. Further, an efficiency analysis shows that the proposed DRM has a lower computational complexity than the state of the art learning-to-diversify methods

Diversity Spectra of Spatial Multipath Fading Processes

We analyse the spatial diversity of a multipath fading process for a finite region or curve in the plane. By means of the Karhunen-Lo\`eve (KL) expansion, this diversity can be characterised by the eigenvalue spectrum of the spatial autocorrelation kernel. This justifies to use the term diversity spectrum for it. We show how the diversity spectrum can be calculated for any such geometrical object and any fading statistics represented by the power azimuth spectrum (PAS). We give rigorous estimates for the accuracy of the numerically calculated eigenvalues. The numerically calculated diversity spectra provide useful hints for the optimisation of the geometry of an antenna array. Furthermore, for a channel coded system, they allow to evaluate the time interleaving depth that is necessary to exploit the diversity gain of the code.Comment: 32 pages, 10 figure