Relevant bibliographies by topics / BDG inequality

Academic literature on the topic 'BDG inequality'

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Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "BDG inequality"

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Sandy, J. "Inequality in uptake of orthodontics." British Dental Journal 202, no. 6 (March 2007): 326–27. http://dx.doi.org/10.1038/bdj.2007.240.

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Drugan, C. S., S. Hamilton, H. Naqvi, and J. R. Boyles. "Inequality in uptake of orthodontic services." British Dental Journal 202, no. 6 (February 9, 2007): E15. http://dx.doi.org/10.1038/bdj.2007.127.

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Garcia, Stephen M., Avishalom Tor, Max H. Bazerman, and Dale T. Miller. "Profit maximization versus disadvantageous inequality: the impact of self-categorization." Journal of Behavioral Decision Making 18, no. 3 (2005): 187–98. http://dx.doi.org/10.1002/bdm.494.

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Gandhi, Sumirtha, Tulasi Malini Maharatha, Umakant Dash, and Suresh Babu M. "Level of inequality and the role of governance indicators in the coverage of reproductive maternal and child healthcare services: Findings from India." PLOS ONE 16, no. 11 (November 12, 2021): e0258244. http://dx.doi.org/10.1371/journal.pone.0258244.

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Background Diligent monitoring of inequalities in the coverage of essential reproductive, maternal, new-born and child health related (RMNCH) services becomes imperative to smoothen the journey towards Sustainable Development Goals (SDGs). In this study, we aim to measure the magnitude of inequalities in the coverage of RMNCH services. We also made an attempt to divulge the relationship between the various themes of governance and RMNCH indices. Methods We used National Family Health Survey dataset (2015–16) and Public Affairs Index (PAI), 2016 for the analysis. Two summative indices, namely Composite Coverage Index (CCI) and Co-Coverage (Co-Cov) indicator were constructed to measure the RMNCH coverage. Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were employed to measure inequality in the distribution of coverage of RMNCH. In addition, we have used Spearman’s rank correlation matrix to glean the association between governance indicator and coverage indices. Results & conclusions Our study indicates an erratic distribution in the coverage of CCI and Co-Cov across wealth quintiles and state groups. We found that the distribution of RII values for Punjab, Tamil Nadu, and West Bengal hovered around 1. Whereas, RII values for Haryana was 2.01 indicating maximum inequality across wealth quintiles. Furthermore, the essential interventions like adequate antenatal care services (ANC4) and skilled birth attendants (SBA) were the most inequitable interventions, while tetanus toxoid and Bacilli Calmette- Guerin (BCG) were least inequitable. The Spearman’s rank correlation matrix demonstrated a strong and positive correlation between governance indicators and coverage indices.
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Roy, Dipankar, Munmi Sarma, Joydeep Roy, and Kinnor Das. "Determinants of immunisation of children under 2 years of age in Rural Barak Valley: An explorative study." IP International Journal of Medical Paediatrics and Oncology 8, no. 1 (March 15, 2022): 24–30. http://dx.doi.org/10.18231/j.ijmpo.2022.006.

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In 1978, India launched the "Expanded Programme on Immunisation" (EPI) to minimise the prevalence of "Vaccine-Preventable Diseases" (VPDs). Despite years of health and medical progress, children in India continue to suffer from VPDs, and significant disparities in immunisation coverage may be seen among regions, states, socioeconomic groups, and other factors. Barak Valley's socioeconomic and environmental characteristics reveal an overall underdevelopment pattern. Furthermore, in the valley, healthcare services such as comprehensive immunisation institutional delivery are underutilised, resulting in poor immunisation coverage. Despite this evidence, there have been limited studies to identify the factors that influence child immunisation. In this context, this article is a modest attempt to identify and quantify the inequality in socio-economic factors in explaining inequality in Child immunisation in rural Barak Valley. A multistage stratified random sampling was used to collect information on immunisation and related variables by using a pre-tested questionnaire from the universe of children aged between 12-23 months of rural Barak Valley. And, binary logistic regression model has been used to analyse the data and draw inferences. The immunisation coverage is the Barak Valley region is very poor. The highest immunisation coverage has been observed for the BCG vaccine, around 90%. And with 64% coverage, vaccination against measles stands at the bottom of the list. The extent of full immunisation in the valley is not satisfactory at all. Around 54% of children aged 12-23 months have received all the WHO recommended vaccines, implying half of the eligible children are left out. The study identifies religion, a strong cultural affiliation that significantly influences the immunisation coverage of the child. Furthermore, the gender of the child, unequal access to ante-natal care, and birth order of the child are the prime factors associated with inequality in child immunisation in the region.
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Xue, Xiaoming, Chaoshun Li, Suqun Cao, Jinchao Sun, and Liyan Liu. "Fault Diagnosis of Rolling Element Bearings with a Two-Step Scheme Based on Permutation Entropy and Random Forests." Entropy 21, no. 1 (January 21, 2019): 96. http://dx.doi.org/10.3390/e21010096.

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This study presents a two-step fault diagnosis scheme combined with statistical classification and random forests-based classification for rolling element bearings. Considering the inequality of features sensitivity in different diagnosis steps, the proposed method utilizes permutation entropy and variational mode decomposition to depict vibration signals under single scale and multiscale. In the first step, the permutation entropy features on the single scale of original signals are extracted and the statistical classification model based on Chebyshev’s inequality is constructed to detect the faults with a preliminary acquaintance of the bearing condition. In the second step, vibration signals with fault conditions are firstly decomposed into a collection of intrinsic mode functions by using variational mode decomposition and then multiscale permutation entropy features derived from each mono-component are extracted to identify the specific fault types. In order to improve the classification ability of the characteristic data, the out-of-bag estimation of random forests is firstly employed to reelect and refine the original multiscale permutation entropy features. Then the refined features are considered as the input data to train the random forests-based classification model. Finally, the condition data of bearings with different fault conditions are employed to evaluate the performance of the proposed method. The results indicate that the proposed method can effectively identify the working conditions and fault types of rolling element bearings.
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De Oliveira, Alberto. "Financial innovations and sanitation services: the battle between low-income users and shareholders." Bulletin of Geography. Socio-economic Series 47, no. 47 (March 25, 2020): 63–74. http://dx.doi.org/10.2478/bog-2020-0004.

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AbstractThis article aims to show how changes in the model for financing basic sanitation affect social inequality and urban segregation, and to discuss alternatives that minimise the impact these changes have on low-income populations. The investigation focuses on mediations between sanitation policy and general urban policies in the more ample process of valorising capital, involving different scales of geography and forms of state action. Widespread privatisation and public–private partnerships have altered the role that rates charged to users play in financing sanitation systems. This, in turn, has an impact on low-income populations’ access to these systems. The study concludes that new models of financing tend to privilege spaces in the city that are attractive to private capital, and that investments in sanitation are supported by financial innovations that depend on the collective force of remunerating shareholders and maintaining investors’ expectations. Finally, the article approaches solutions that ensure low-income families’ access to public services, with special emphasis on subsidised rate systems based on the stratification of urban areas adopted in Colombia. The article concludes that this experiment presents both positive and negative aspects that may serve as starting points toward potential solutions for Brazil.
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Dangor, Faheem, Gijsbert Hoogendoorn, and Raeesa Moolla. "Medical tourism by Indian-South Africans to India: an exploratory investigation." Bulletin of Geography. Socio-economic Series 29, no. 29 (September 1, 2015): 19–30. http://dx.doi.org/10.1515/bog-2015-0022.

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Abstract Medical tourism is a well-established sector in developing countries, and attracts a significant number of tourists from developed countries. Medical tourism is a strong driver of economic growth, but some argue that this kind of tourism promotes inequality in terms of access to healthcare facilities in both developing and developed countries. Whilst research has been conducted on medical tourists travelling to South Africa, no research has focused on the geography of South Africans travelling abroad for medical tourist activities. This study therefore sought to obtain first-hand information from Indian-South African citizens who have partaken in medical tourism in India. Data was gathered through personal, semi-structured interviews conducted with 54 individuals. It was ascertained that the majority of the individuals interviewed in this study travelled to India primarily for medical treatment, while tourist activities were a secondary objective. A smaller proportion of interviewees travelled to India for vacation, with medical care being a secondary motivation, or an impulse due to the low cost of treatment and convenience. Medical tourism by Indian-South Africans travelling to India highlights various shortfalls in South African medical care, including a lack of treatment availability, a poorer quality of service, medical expertise abroad, and the higher cost incurred locally.
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Kong, Jude Dzevela, Ugochukwu Ejike Akpudo, Jake Okechukwu Effoduh, and Nicola Luigi Bragazzi. "Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South." Healthcare 11, no. 4 (February 4, 2023): 457. http://dx.doi.org/10.3390/healthcare11040457.

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In the present paper, we will explore how artificial intelligence (AI) and big data analytics (BDA) can help address clinical public and global health needs in the Global South, leveraging and capitalizing on our experience with the “Africa-Canada Artificial Intelligence and Data Innovation Consortium” (ACADIC) Project in the Global South, and focusing on the ethical and regulatory challenges we had to face. “Clinical public health” can be defined as an interdisciplinary field, at the intersection of clinical medicine and public health, whilst “clinical global health” is the practice of clinical public health with a special focus on health issue management in resource-limited settings and contexts, including the Global South. As such, clinical public and global health represent vital approaches, instrumental in (i) applying a community/population perspective to clinical practice as well as a clinical lens to community/population health, (ii) identifying health needs both at the individual and community/population levels, (iii) systematically addressing the determinants of health, including the social and structural ones, (iv) reaching the goals of population’s health and well-being, especially of socially vulnerable, underserved communities, (v) better coordinating and integrating the delivery of healthcare provisions, (vi) strengthening health promotion, health protection, and health equity, and (vii) closing gender inequality and other (ethnic and socio-economic) disparities and gaps. Clinical public and global health are called to respond to the more pressing healthcare needs and challenges of our contemporary society, for which AI and BDA can help unlock new options and perspectives. In the aftermath of the still ongoing COVID-19 pandemic, the future trend of AI and BDA in the healthcare field will be devoted to building a more healthy, resilient society, able to face several challenges arising from globally networked hyper-risks, including ageing, multimorbidity, chronic disease accumulation, and climate change.
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Mikhaylov, Andrey, Anna Mikhaylova, Kamil Alsynbaev, Vitaliy Bryksin, and Dmitry Hvaley. "Remote-sensing technology in mapping socio-economic divergence of Europe." Bulletin of Geography. Socio-economic Series 52, no. 52 (June 1, 2021): 69–84. http://dx.doi.org/10.2478/bog-2021-0014.

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Abstract Marine and ocean coasts traditionally act as natural growth poles for humankind. Recent studies conducted by scholars from both natural and social sciences suggest that coastal zones accumulate population, agglomerate industries, attract entrepreneurs, and pull investments. The coastalisation effect remains one of the defining factors of regional development around the globe and is projected to strengthen over the next quarter century. Deepening socio-economic inequality and polarisation between countries and regions despite efforts taken with convergence policies put the “marine factor” on the research agenda. The study contains a comparative evaluation of coastalisation processes across the regions of Europe using remote-sensing technology and statistical multivariate analysis for testing the correlation level of results. The research is based on a dataset for 413 regions of Europe featuring indicators for population density and Gross Regional Product (GRP) in Purchasing Power Parity (PPP) per sq. km. The regions are grouped into clusters depending on their socio-economic indicators and the intensity of nocturnal illumination. The results suggest that coastal and inland region types evenly distribute between clusters, with an average of 40% coastal. Observations of nocturnal illumination clearly indicate an extensive anthropogenic impact on European coasts, both northern and southern. However, their overall luminosity is inferior to inland territories. The study concludes with four patterns derived from a combined methodology of socio-economic indicators and remote-sensing of night-time lighting.
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Dissertations / Theses on the topic "BDG inequality"

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IBRAGIMOV, ANTON. "G - Expectations in infinite dimensional spaces and related PDES." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/44738.

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In this thesis, we extend the G-expectation theory to infinite dimensions. Such notions as a covariation set of G-normal distributed random variables, viscosity solution, a stochastic integral drive by G-Brownian motion are introduced and described in the given infinite dimensional case. We also give a probabilistic representation of the unique viscosity solution to the fully nonlinear parabolic PDE with unbounded first order term in Hilbert space in terms of G-expectation theory.
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Hayman, Bernard Akeem. "Community, Identity, and Agency in the Age of Big Social Data: A Place-based Study on Literacies, Perceptions, and Responses of Digital Engagement." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1586602013429227.

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Czarnecki, Lukasz. "Configuration du pouvoir et reproduction de la pauvreté et des inégalités dans quatre États mexicains : Chiapas, Veracruz, Yucatan et District Fédéral." Thesis, Strasbourg, 2015. http://www.theses.fr/2015STRAG019.

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L’objectif principal de cette étude est d’analyser la configuration du pouvoir local dans quatre États mexicains : le Chiapas, le Veracruz, le Yucatan et le District Fédéral, en lien avec la reproduction de la pauvreté et des inégalités, qui persistent en dépit de la mise en œuvre de programmes sociaux destinés aux personnes âgées du pays. Ces quatre États mexicains montrent des similitudes et des différences dans la reproduction du pouvoir par le PRI (Partido Revolucionario Institucional) et par les « grandes familles ». Cette reproduction est à mettre en relation avec le clientélisme politique, qui alimente également la reproduction de la pauvreté et des inégalités. L’étude comparative entre ces quatre États est réalisée dans un contexte de transition sociodémographique et de vieillissement de la population mexicaine. L’étude aborde également les questions de la discrimination du genre, des relations conflictuelles entre classes sociales et du racisme dans les rapports sociaux, en articulation avec la persistance du « colonialisme du pouvoir » mis en œuvre par différents groupes exogènes et endogènes
The main objective of this study is to analyze the local power configuration in four Mexican states: Chiapas, Veracruz, Yucatan and the Federal District, with regard to reproduction of poverty and inequality that persist despite the implementation of social programs for the elderly in Mexico. These four Mexican states show similarities and differences in the reproduction of power by the PRI (Partido Revolucionario Institucional) and by the "big families". This reproduction is related to political clientelism, which also supplies the reproduction of poverty and inequality. The comparative study between four states is carried out within a context of socio-demographic transition and ageing processes of Mexican population. The study also addresses issues of gender discrimination, conflicts between social classes and racism in social relations, in articulation with persistence of the "colonialism of power" implemented by various exogenous and endogenous groups
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Khayyat, Zuhair. "Scaling Big Data Cleansing." Diss., 2017. http://hdl.handle.net/10754/625281.

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Data cleansing approaches have usually focused on detecting and fixing errors with little attention to big data scaling. This presents a serious impediment since identify- ing and repairing dirty data often involves processing huge input datasets, handling sophisticated error discovery approaches and managing huge arbitrary errors. With large datasets, error detection becomes overly expensive and complicated especially when considering user-defined functions. Furthermore, a distinctive algorithm is de- sired to optimize inequality joins in sophisticated error discovery rather than na ̈ıvely parallelizing them. Also, when repairing large errors, their skewed distribution may obstruct effective error repairs. In this dissertation, I present solutions to overcome the above three problems in scaling data cleansing. First, I present BigDansing as a general system to tackle efficiency, scalability, and ease-of-use issues in data cleansing for Big Data. It automatically parallelizes the user’s code on top of general-purpose distributed platforms. Its programming inter- face allows users to express data quality rules independently from the requirements of parallel and distributed environments. Without sacrificing their quality, BigDans- ing also enables parallel execution of serial repair algorithms by exploiting the graph representation of discovered errors. The experimental results show that BigDansing outperforms existing baselines up to more than two orders of magnitude. Although BigDansing scales cleansing jobs, it still lacks the ability to handle sophisticated error discovery requiring inequality joins. Therefore, I developed IEJoin as an algorithm for fast inequality joins. It is based on sorted arrays and space efficient bit-arrays to reduce the problem’s search space. By comparing IEJoin against well- known optimizations, I show that it is more scalable, and several orders of magnitude faster. BigDansing depends on vertex-centric graph systems, i.e., Pregel, to efficiently store and process discovered errors. Although Pregel scales general-purpose graph computations, it is not able to handle skewed workloads efficiently. Therefore, I introduce Mizan, a Pregel system that balances the workload transparently during runtime to adapt for changes in computing needs. Mizan is general; it does not assume any a priori knowledge of the graph structure or the algorithm behavior. Through extensive evaluations, I show that Mizan provides up to 84% improvement over techniques leveraging static graph pre-partitioning.
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Books on the topic "BDG inequality"

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Inequality and the global economic crisis / Douglas Dowd. London: Pluto Press, 2009.

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O'Neil, Cathy. Weapons of Math Destruction: How big data increases inequality and threatens democracy. Great Britain: Allen Lane, 2016.

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O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group NY, 2016.

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O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Broadway Books, 2016.

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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. USA: Broadway Books, 2017.

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O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Penguin Books, Limited, 2016.

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O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Penguin, 2017.

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O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Pub, 2016.

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Brayne, Sarah. Predict and Surveil. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190684099.001.0001.

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The scope of criminal justice surveillance, from policing to incarceration, has expanded rapidly in recent decades. At the same time, the use of big data has spread across a range of fields, including finance, politics, health, and marketing. While law enforcement’s use of big data is hotly contested, very little is known about how the police actually use it in daily operations and with what consequences. This book offers an inside look at how police use big data and new surveillance technologies, leveraging on-the-ground fieldwork with one of the most technologically advanced law enforcement agencies in the world—the Los Angeles Police Department. Drawing on original interviews and ethnographic observations from over two years of fieldwork with the LAPD, the text examines the causes and consequences of big data and algorithmic control. It reveals how the police use predictive analytics and new surveillance technologies to deploy resources, identify criminal suspects, and conduct investigations; how the adoption of big data analytics transforms police organizational practices; and how the police themselves respond to these new data-driven practices. While big data analytics has the potential to reduce bias, increase efficiency, and improve prediction accuracy, the book argues that it also reproduces and deepens existing patterns of inequality, threatens privacy, and challenges civil liberties.
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Jacobs, Lawrence, and Desmond King. Fed Power. 2nd ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197573129.001.0001.

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The Federal Reserve, created more than a century ago, is the most powerful central bank in the world. The Fed’s power to alter the money supply, move interest rates, and to intervene to save Wall Street and large corporations helps many Americans, but not equally. Specific industries in finance and large businesses reap lopsided and often concealed benefits while homeowners, workers, and Americans of color slip further behind. The substantial expansion of the Fed’s power circumvents America’s constitutional checks and contributes to economic inequality and racial disparities. The second edition of Lawrence R. Jacobs and Desmond King’s Fed Power extends their decisive account of the Fed’s favoritism toward Wall Street and big business during the 2008–2009 financial crisis to the Fed’s unprecedented responses to the economic collapse sparked by the coronavirus pandemic in 2020. In five chapters, Jacobs and King discuss the origins of the Federal Reserve System, its maneuvering to advance its capacity and autonomy to act independent of Congress and the presidency, and unprecedented support for Wall Street and big business during in the crises in 2008–2009 and 2020. Fed Power analyses how the scale of the Fed’s economic interventions since 2008 is provoking public unease, organized protests and advocacy, and congressional pressure for reform. The deadly coronavirus and the Movement for Black Lives are intensifying the push for democratic accountability, stringent regulation of banks, and new policies to reduce economic inequality and Black-White disparities. Fed Power is a corrective to both the Bank’s self-serving claims of serving the public even as it favors the best-off, and the reluctance of researchers to recognize the Fed’s role in America’s racial and economic inequalities.
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Book chapters on the topic "BDG inequality"

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Hinkis, Arie. "Tarski’s Proofs of BDT and the Inequality-BDT." In Proofs of the Cantor-Bernstein Theorem, 335–42. Basel: Springer Basel, 2012. http://dx.doi.org/10.1007/978-3-0348-0224-6_34.

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Gamper, Markus, and Annett Kupfer. "Migration as a Health Inequality Dimension? Natio-Ethno-Cultural Affiliation, Health, and Social Networks." In Social Networks and Health Inequalities, 291–324. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97722-1_16.

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AbstractConcepts like race, migration background, or ethnic group are more and more being investigated in health research. It should be noted that those concepts themselves are very heterogeneous. They are, for example, endowed with different rights (e.g., cosmopolitan migrants from the global north, refugees from the global south) (Ambrosini & van der Leun, 2015) or have to deal with racism or discrimination (Nazroo, 2003). A challenge and a recurrent difficulty in research on the health of migrants is the operationalization of studies due to the heterogeneity of the group. On the one hand, it is unclear which criteria—nationality, mother tongue, ethnicity of grandparents, race, place of birth, place of migration as well as migration regime—are used to determine “migrants,” which makes comparability of the studies difficult (Sheldon & Parker, 1992). On the other hand, the group of people with a history of migration is very heterogeneous with regard to other lines of difference, such as social milieu/class and gender, but also country of origin and reason and time of migration. This makes the health situation of the so-called migrants very different, and it cannot be described in a generalized way. Research shows that social integration and social support can play a big role in the health status of migrants. It can provide information to the healthcare system, provide emotional support, or simply make someone feel like they are not alone. Social networks also play a big role for people with a so-called migration background or with a so-called different ethnic background (Johnson et al., 2017). In this chapter, we explore the link between health, migration, and networks. In doing so, we will try to minimize the uncertainty of the heterogeneity of the group as much as possible.
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Molnar, Petra. "Territorial and Digital Borders and Migrant Vulnerability Under a Pandemic Crisis." In Migration and Pandemics, 45–64. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81210-2_3.

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AbstractPeople on the move are often left out of conversations around technological development and become guinea pigs for testing new surveillance tools before bringing them to the wider population. These experiments range from big data predictions about population movements in humanitarian crises to automated decision-making in immigration and refugee applications to AI lie detectors at European airports. The Covid-19 pandemic has seen an increase of technological solutions presented as viable ways to stop its spread. Governments’ move toward biosurveillance has increased tracking, automated drones, and other technologies that purport to manage migration. However, refugees and people crossing borders are disproportionately targeted, with far-reaching impacts on various human rights. Drawing on interviews with affected communities in Belgium and Greece in 2020, this chapter explores how technological experiments on refugees are often discriminatory, breach privacy, and endanger lives. Lack of regulation of such technological experimentation and a pre-existing opaque decision-making ecosystem creates a governance gap that leaves room for far-reaching human rights impacts in this time of exception, with private sector interest setting the agenda. Blanket technological solutions do not address the root causes of displacement, forced migration, and economic inequality – all factors exacerbating the vulnerabilities communities on the move face in these pandemic times.
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"Digital Inequality." In Encyclopedia of Big Data, 387. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-32010-6_300088.

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Brayne, Sarah. "Coding Inequality." In Predict and Surveil, 100–117. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190684099.003.0006.

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This chapter looks at the promise and peril of police use of big data analytics for inequality. On the one hand, big data analytics may be a means by which to ameliorate persistent inequalities in policing. Data can be used to “police the police” and replace unparticularized suspicion of racial minorities and human exaggeration of patterns with less biased predictions of risk. On the other hand, data-intensive police surveillance practices are implicated in the reproduction of inequality in at least four ways: by deepening the surveillance of individuals already under suspicion, codifying a secondary surveillance network of individuals with no direct police contact, widening the criminal justice dragnet unequally, and leading people to avoid institutions that collect data and are fundamental to social integration. Crucially, as currently implemented, “data-driven” decision-making techwashes, both obscuring and amplifying social inequalities under a patina of objectivity.
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Wade, Robert. "Inequality and the West." In BWB Texts: Big Issues. Bridget Williams Books, 2014. http://dx.doi.org/10.7810/9781927327982_4.

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"Macroeconomists, Efficiency, and Inequality." In Big Ideas in Macroeconomics. The MIT Press, 2013. http://dx.doi.org/10.7551/mitpress/9380.003.0005.

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Athreya, Kartik B. "Macroeconomists, Efficiency, and Inequality." In Big Ideas in Macroeconomics, 121–56. The MIT Press, 2013. http://dx.doi.org/10.7551/mitpress/9780262019736.003.0004.

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Chen, Yunsong, Guangye He, and Fei Yan. "Public concerns about class immobility and economic inequality." In Understanding China through Big Data, 34–50. Routledge, 2021. http://dx.doi.org/10.4324/9781003164166-5.

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Zattler, Jürgen Karl. "Inequality, Financialisation, and Risks to the Earth System." In Practice, Progress, and Proficiency in Sustainability, 1–17. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0440-5.ch001.

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This chapter examines the issue of growing inequality in developing countries. The first section of this chapter highlights a few key facts regarding the evolution of inequality. The second session asks why equality matters. The third session focusses on the driving forces behind the growing inequality. The fourth section outlines implications for developing countries and their development strategies. The final section focusses on possible international initiatives which might mobilize “green” investments at big scale and foster equality at the same time.
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Conference papers on the topic "BDG inequality"

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Chitrakar, Ambika Shrestha, and Slobodan Petrovic. "Analyzing Digital Evidence Using Parallel k-means with Triangle Inequality on Spark." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622430.

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Li, Yiming, Yue Xue, Kaichen Song, and Silu Wang. "Globalization and Income Inequality: Comparative Analysis of 83 Countries." In The International Conference on Big Data Economy and Digital Management. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0011186400003440.

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Satyanarayana, Ashwin. "Intelligent sampling for big data using bootstrap sampling and chebyshev inequality." In 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2014. http://dx.doi.org/10.1109/ccece.2014.6901029.

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Posada, Alejandro, and George Chen. "Inequality in Knowledge Production: The Integration of Academic Infrastructure by Big Publishers." In 22nd International Conference on Electronic Publishing. OpenEdition Press, 2018. http://dx.doi.org/10.4000/proceedings.elpub.2018.30.

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Zhang, Yongqi, and Jingzhi Cao. "Factor Market Distortions and Rural Information Inequality: Based on Empirical Analysis." In The International Conference on Big Data Economy and Digital Management. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0011232100003440.

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Ghamdi, Sami Al, and Giuseppe Di Fatta. "Efficient Parallel K-Means on MapReduce Using Triangle Inequality." In 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). IEEE, 2017. http://dx.doi.org/10.1109/dasc-picom-datacom-cyberscitec.2017.163.

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Cai, Yijin, Jiachen Shi, Xuefei Ma, and Lan Xiao. "Globalization and income inequality: A comparative study of panel data approach for the EU countries." In 2021 3rd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI). IEEE, 2021. http://dx.doi.org/10.1109/mlbdbi54094.2021.00071.

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Zhu, Xiaoning, Jun Liu, and Tingting Li. "A Study of Social Integration of Urban Household Migrants from the Perspective of Social Exclusion: An Empirical Analysis based on Housing Inequality." In International Conference on Public Management and Big Data Analysis. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0011151400003437.

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Ren, Jingru. "An Empirical Study on the Changes in Health Inequality of Chinese Residents: based on data from China Health and Nutrition Survey." In 2021 International Conference on Health Big Data and Smart Sports (HBDSS). IEEE, 2021. http://dx.doi.org/10.1109/hbdss54392.2021.00017.

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Fynchina, Khicheza. "The Tax Burden as a Criterion for the Reform in Tax System of the Kyrgyz Republic." In International Conference on Eurasian Economies. Eurasian Economists Association, 2013. http://dx.doi.org/10.36880/c04.00613.

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Abstract:
The most revealing criterion of effectiveness of tax reforms is the level of the tax burden. Optimal way to estimate sectoral tax burden is to use tax burden coefficient for a newly created value. Other indicators of tax burden differ because of over detailing which doesn’t allow making right accentuation in analytical conclusion. This idea is supported by Chick:“in complicated system, the results gained by detailed investigation of particular aspects can’t be generalized over the whole issue of the research…” (Chick, 1864). Based on this, the analysis of structure and the level of tax burden in different branches of economics of the Kyrgyz Republic for the period of 2005 through 2011 was conducted. It was found that main tax burden carries the industry with big inequality. The main tax burden in Kyrgyzstan falls on mineral resource industry (coefficient of tax burden an average of 30), while in manufacturing industry it is one of the lowest indexes (0,68) and in health care (0,63). The structure of tax burden has changed in relation to the introduction of sales tax. In addition there is a big portion in tax burden among almost all sectors of economics and VAT (for domestic products). The ways to reform the tax system are: the harmonization of indirect taxes (for example through the cancellation of the sales tax while increasing the rate of VAT), review of tax exemptions, conditions and methods of supply, the list of taxable supplies, as well as the principles for determining excise goods.
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