Showing papers on "Diversity (politics) published in 2022"

The Experience of Nature

Abstract: Why do we1 want to keep anything? Surely it is because it means something to us? Isn’t it because we value qualities like usefulness and the ways in which we can cherish memories and meaningful associations? We may keep things which make life easier, help us in day-to-day living and might assist us in some future difficult time. We may also value those things with enriching associations – something we found on a memorable day; something which appealed to us for its form and beauty, its intricacy, diversity or simplicity; something inherited from an ancestor or given to us by a friend or parent. Or it can be something we did not know about but which we found out about in the media or which a teacher, parent or mentor told us was rare, valuable, a privilege to have. Thus, the meaning can be discovered by yourself or a meaning can be given to you by someone else which then becomes significant to you. Whatever the many reasons for keeping something, it is the value and the meanings which make us cherish it: the meanings vary widely, but meanings there have to be. Hence the subtitle of the book: Perspectives on Meanings and Motivations. Meanings are the key.

Pluralities

Abstract: Plurality is a conceptual tool that makes diversity explicit. Its importance lies in the theoretical field of studies. Plurality encompasses social values, collective lifestyle, ethics, respect, justice, knowledge of various cultures, and the impact of physical and psychological suffering created by prejudice and discrimination. Understanding the different types of knowledge and the mechanisms that keep them concealed and that affect them can contribute to reducing prejudice, fear, and insecurity in the face of the unknown. A confrontation occurs in the presence of insecurity. Fear and anger emerge, and violence becomes an act of eliminating that which is considered threatening. Moreover, the contemporary context adds technology, competition, and speed to this equation, and the result impacts our lives, disconnects us, and anesthetizes our social and emotional bodies. As a principle of plurality, diversity is key to our lives. There is no survival without transformation. We and the world are in constant change. This involves action, learning, and both personal and social experience.

Gender-diverse teams produce more novel and higher-impact scientific ideas

Abstract: Significance Science teams made up of men and women produce papers that are more novel and highly cited than those of all-men or all-women teams. These performance advantages increase the greater the team’s gender balance and appear nearly universal. On average, they hold for small and large teams, the 45 subfields of medicine, and women- or men-led teams and generalize to published papers in all science fields over the last 20 y. Notwithstanding these benefits, gender-diverse teams remain underrepresented in science when compared to what is expected if the teams in the data had been formed without regard to gender. These findings reveal potentially new gender and teamwork synergies that correlate with scientific discoveries and inform diversity, equity, and inclusion (DEI) initiatives.

Combating Structural Inequities — Diversity, Equity, and Inclusion in Clinical and Translational Research

Abstract: Interview with Dr. L. Ebony Boulware on the importance of racial and ethnic diversification and increased focus on equity in clinical and translational research. (13:19)Download If the clinical and translational research enterprise is to help resolve health crises and ensure that all people in the United States have the opportunity to live healthy lives, it must shift paradigms and begin to center equity, diversity, and inclusion in its work.

Data augmentation approaches in natural language processing: A survey

Abstract: As an effective strategy, data augmentation (DA) alleviates data scarcity scenarios where deep learning techniques may fail. It is widely applied in computer vision then introduced to natural language processing and achieves improvements in many tasks. One of the main focuses of the DA methods is to improve the diversity of training data, thereby helping the model to better generalize to unseen testing data. In this survey, we frame DA methods into three categories based on the diversity of augmented data, including paraphrasing, noising, and sampling. Our paper sets out to analyze DA methods in detail according to the above categories. Further, we also introduce their applications in NLP tasks as well as the challenges. Some helpful resources are provided in the appendix.

The giant plan to track diversity in research journals

Abstract: Efforts to chart and reduce bias in scholarly publishing will ask authors, reviewers and editors to disclose their race or ethnicity. Efforts to chart and reduce bias in scholarly publishing will ask authors, reviewers and editors to disclose their race or ethnicity.

Digital transformation and corporate environmental performance: The moderating role of board characteristics

Abstract: Digital transformation, board characteristics, and environmental performance are increasingly important in the field of corporate sustainability. However, despite the growing literature on digital transformation, there is a paucity of literature that considers board characteristics. This paper aims to fill this gap by exploring the relationship between digital transformation and environmental performance from the perspective of board characteristics. Chinese listed companies from 2010 to 2019 were taken as the original data, the moderating effect of the board characteristics was tested by using the moderating effect model. We find that digital transformation can significantly improve corporate environmental performance. A low willingness to digital transformation was showed in the board of directors with age diversity, nationality diversity, shareholding concentration, and political connections. In contrast, digital transformation strategies were preferred in the boards with more female directors and higher educational backgrounds. Our study is of significant value for companies undergoing digital transformation.

Diversity Training Goals, Limitations, and Promise: A Review of the Multidisciplinary Literature

Abstract: In this review, we utilize a narrative approach to synthesize the multidisciplinary literature on diversity training. In examining hundreds of articles on the topic, we discovered that the literature is amorphous and complex and does not allow us to reach decisive conclusions regarding best practices in diversity training. We note that scholars of diversity training, when testing the efficacy of their approaches, too often use proxy measures for success that are far removed from the types of consequential outcomes that reflect the purported goals of such trainings. We suggest that the enthusiasm for, and monetary investment in, diversity training has outpaced the available evidence that such programs are effective in achieving their goals. We recommend that researchers and practitioners work together for future investigations to propel the science of diversity training forward. We conclude with a roadmap for how to create a more rigorous and relevant science of diversity training.

Recommender systems effect on the evolution of users’ choices distribution

Abstract: Recommender systems’ (RSs) research has mostly focused on algorithms aimed at improving platform owners’ revenues and user’s satisfaction. However, RSs have additional effects, which are related to their impact on users’ choices. In order to avoid an undesired system behaviour and anticipate the effects of an RS, the literature suggests employing simulations. In this article we present a novel, well grounded and flexible simulation framework. We adopt a stochastic user’s choice model and simulate users’ repeated choices for items in the presence of alternative RSs. Properties of the simulated choices, such as their diversity and their quality, are analysed. We state four research questions, also motivated by identified research gaps, which are addressed by conducting an experimental study where three different data sets and five alternative RSs are used. We identify some important effects of RSs. We find that non-personalised RSs result in choices for items that have a larger predicted rating compared to personalised RSs. Moreover, when a user’s awareness set, which is the set containing the items that she can choose from, increases, then choices are more diverse, but the average quality (rating) of the choices decreases. Additionally, in order to achieve a higher choice diversity, increasing the awareness of the users is shown to be a more effective remedy than increasing the number of recommendations offered to the users.

Rare Species-Driven Diversity–Ecosystem Multifunctionality Relationships are Promoted by Stochastic Community Assembly

Abstract: The relative functional importance of rare and abundant species in driving relationships between biodiversity and ecosystem functions remains unknown. Here, we highlighted the importance of rare species for ecosystem multifunctionality. ABSTRACT The relative functional importance of rare and abundant species in driving relationships between biodiversity and ecosystem functions (BEF) remains unknown. Here, we investigated the functional roles of rare and abundant species diversity (multitrophic soil organism groups) on multifunctionality derived from 16 ecosystem functions in 228 agricultural fields relating to soil and crop health. The results revealed that the diversity of rare species, rather than of abundant species, was positively related to multifunctionality. Abundant taxa tended to maintain a larger number of functions than rare taxa, while rare subcommunity contributed more phylotypes supporting to the single ecosystem functions. Community assembly processes were closely related to the ecosystem functional performance of soil biodiversity, only observed in rare subcommunity. Higher relative contributions of stochastic assembly processes promoted the positive effects of diversity of rare taxa on multifunctionality, while reducing their diversity and multifunctionality overall. Our results highlight the importance of rare species for ecosystem multifunctionality and elucidate the linkage between ecological assembly processes and BEF relationships. IMPORTANCE The relative functional importance of rare and abundant species in driving relationships between biodiversity and ecosystem functions remains unknown. Here, we highlighted the importance of rare species for ecosystem multifunctionality. In addition, community assembly processes were closely related to the ecosystem functional performance of soil biodiversity in rare subcommunity. Stochastic assembly processes promoted the positive effects of diversity of rare taxa on multifunctionality, while reducing their diversity and multifunctionality overall. This study expands current understanding of the mechanisms underpinning the relationships between biodiversity and ecosystem functions and suggests that stochastic community assembly enhances BEF relationships.

Business Digital Maturity in Europe and Its Implication for Open Innovation

Abstract: This paper presents the results of a study aimed at assessing the level of business digital maturity in Europe and at analyzing similarities between companies in terms of implemented Industry 4.0 technologies. The digital transformation of production and service enterprises has become a common direction of development for all economic sectors. The very idea of Industry 4.0 has become synonymous with innovation and is the basis for business development. The role and importance of these transformations are also recognized by the EU which has been promoting and supporting the development of an innovative digital economy for many years. However, individual EU countries differ in terms of digital business maturity due to the implementation of Industry 4.0 technology. The article addresses this problem by presenting the results of a comprehensive study of the implementation of Industry 4.0 digital technologies in enterprises in the EU-27 countries and by assessing similarities between these countries in terms of these technologies. The similarity analysis was carried out using the k-means method. The Gini coefficient and Lorenz curves were utilized to determine the unevenness of the implementation of these technologies in individual countries, and the Weighted Aggregated Sum Product Assessment method was used to assess the level of digital maturity. The research was based on eight selected determinants (indicators) that characterize the most important technologies related to Industry 4.0. The results showed high diversity among EU countries in terms of digital maturity. Scandinavian countries (Finland and Denmark) and Malta were found to be leaders in this area, while the weakest results were reported for Greece, Romania, Bulgaria, Hungary, and Latvia. The findings provide a lot of new information about the current state of development of the digital economy in EU countries, which should be used in both the development and implementation of new solutions related to economic digitalization policy in this region.

Approximating gradients for differentiable quality diversity in reinforcement learning

Abstract: Consider the problem of training robustly capable agents. One approach is to generate a diverse collection of agent polices. Training can then be viewed as a quality diversity (QD) optimization problem, where we search for a collection of performant policies that are diverse with respect to quantified behavior. Recent work shows that differentiable quality diversity (DQD) algorithms greatly accelerate QD optimization when exact gradients are available. However, agent policies typically assume that the environment is not differentiable. To apply DQD algorithms to training agent policies, we must approximate gradients for performance and behavior. We propose two variants of the current state-of-the-art DQD algorithm that compute gradients via approximation methods common in reinforcement learning (RL). We evaluate our approach on four simulated locomotion tasks. One variant achieves results comparable to the current state-of-the-art in combining QD and RL, while the other performs comparably in two locomotion tasks. These results provide insight into the limitations of current DQD algorithms in domains where gradients must be approximated. Source code is available at https://github.com/icaros-usc/dqd-rl

Light olefin synthesis from a diversity of renewable and fossil feedstocks: state-of the-art and outlook.

Abstract: Light olefins are important feedstocks and platform molecules for the chemical industry. Their synthesis has been a research priority in both academia and industry. There are many different approaches to the synthesis of these compounds, which differ by the choice of raw materials, catalysts and reaction conditions. The goals of this review are to highlight the most recent trends in light olefin synthesis and to perform a comparative analysis of different synthetic routes using several quantitative characteristics: selectivity, productivity, severity of operating conditions, stability, technological maturity and sustainability. Traditionally, on an industrial scale, the cracking of oil fractions has been used to produce light olefins. Methanol-to-olefins, alkane direct or oxidative dehydrogenation technologies have great potential in the short term and have already reached scientific and technological maturities. Major progress should be made in the field of methanol-mediated CO and CO2 direct hydrogenation to light olefins. The electrocatalytic reduction of CO2 to light olefins is a very attractive process in the long run due to the low reaction temperature and possible use of sustainable electricity. The application of modern concepts such as electricity-driven process intensification, looping, CO2 management and nanoscale catalyst design should lead in the near future to more environmentally friendly, energy efficient and selective large-scale technologies for light olefin synthesis.

Multilateral benefit-sharing from digital sequence information will support both science and biodiversity conservation

Abstract: Open access to sequence data is a cornerstone of biology and biodiversity research, but has created tension under the United Nations Convention on Biological Diversity (CBD). Policy decisions could compromise research and development, unless a practical multilateral solution is implemented. Ensuring international benefit-sharing from sequence data without jeopardising open sharing is a major obstacle for the Convention on Biological Diversity and other UN negotiations. Here, the authors propose a solution to address the concerns of both developing countries and life scientists.

Faculty Recruitment, Retention, and Representation in Leadership: An Evidence-Based Guide to Best Practices for Diversity, Equity, and Inclusion from the Council of Residency Directors in Emergency Medicine

Abstract: Improving the recruitment, retention, and leadership advancement of faculty who are under-represented in medicine is a priority at many academic institutions to ensure excellence in patient care, research, and health equity. Here we provide a critical review of the literature and offer evidence-based guidelines for faculty recruitment, retention, and representation in leadership. Recommendations for recruitment include targeted recruitment to expand the candidate pool with diverse candidates, holistic review of applications, and incentivizing stakeholders for success with diversity efforts. Retention efforts should establish a culture of inclusivity, promote faculty development, and evaluate for biases in the promotion and tenure process. We believe this guide will be valuable for all leaders and faculty members seeking to advance diversity, equity, and inclusion in their institutions.

Cohort Profile: The Zurich Project on the Social Development from Childhood to Adulthood (z-proso)

Abstract: The Zurich Project on the Social Development from Childhood to Adulthood (z-proso) began in 2004 in response to the need for a better evidence base to support optimal child social development and prevent crime and violence. Since then, the study has tracked the development of a diverse sample of youths (N = 1,675 in the target sample; ~50% female) from age 7 (n = 1,360) to age 20 (n = 1,180), with primary data collection waves at ages 7, 8, 9, 10, 11, 12, 13, 15, 17, and 20. The study uses a multi-method, multi-informant design that combines teacher, youth, and parent reports with observational and behavioural measures, biosampling, functional imaging, and ecological momentary assessment. Analyses of the data have contributed important evidence to a diversity of topics in child and adolescent development, illuminating the developmental roots of crime and aggression, the impacts of exposure to different forms and combinations of victimisation, and trajectories of mental health and neurodevelopmental symptoms.