A Guidebook on Mapping Poverty Through Data Integration and Artificial Intelligence PDF Download
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Author: Asian Development Bank
Publisher:
ISBN: 9789292627850
Category :
Languages : en
Pages : 274
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Book Description
This guidebook identifies tools and resources that can help generate poverty statistics using satellite imagery, geospatial data, and machine-learning algorithms to augment conventional data collection and sample survey techniques. The "leave no one behind" principle of the 2030 Agenda for Sustainable Development requires appropriate indicators to be estimated for different segments of a country's population. The guidebook was based on a feasibility study by ADB, in collaboration with the Philippine Statistics Authority, the National Statistical Office of Thailand, and the World Data Lab, that aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics. It also serves as an accompanying guide to the Key Indicators for Asia and the Pacific 2020 special supplement focusing on mapping poverty estimates.
Author: Asian Development Bank
Publisher:
ISBN: 9789292627850
Category :
Languages : en
Pages : 274
Get Book Here
Book Description
This guidebook identifies tools and resources that can help generate poverty statistics using satellite imagery, geospatial data, and machine-learning algorithms to augment conventional data collection and sample survey techniques. The "leave no one behind" principle of the 2030 Agenda for Sustainable Development requires appropriate indicators to be estimated for different segments of a country's population. The guidebook was based on a feasibility study by ADB, in collaboration with the Philippine Statistics Authority, the National Statistical Office of Thailand, and the World Data Lab, that aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics. It also serves as an accompanying guide to the Key Indicators for Asia and the Pacific 2020 special supplement focusing on mapping poverty estimates.
Author: Asian Development Bank
Publisher: Asian Development Bank
ISBN: 9292627759
Category : Business & Economics
Languages : en
Pages : 137
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Book Description
The "leave no one behind" principle espoused by the 2030 Agenda for Sustainable Development requires measures of progress for different segments of the population. This entails detailed disaggregated data to identify subgroups that might be falling behind, to ensure progress toward achieving the Sustainable Development Goals (SDGs). The Asian Development Bank and the Statistics Division of the United Nations Department of Economic and Social Affairs developed this practical guidebook with tools to collect, compile, analyze, and disseminate disaggregated data. It also provides materials on issues and experiences of countries regarding data disaggregation for the SDGs. This guidebook is for statisticians and analysts from planning and sector ministries involved in the production, analysis, and communication of disaggregated data.
Author:
Publisher:
ISBN: 9789292623142
Category : Artificial intelligence
Languages : en
Pages : 54
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Book Description
This special supplement to the Key Indicators for Asia and the Pacific 2020 discusses how poverty estimates can be enhanced by integrating household surveys and censuses with data extracted from satellite imagery.
Author: Asian Development Bank
Publisher:
ISBN: 9789292623135
Category :
Languages : en
Pages : 54
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Book Description
This special supplement to the Key Indicators for Asia and the Pacific 2020 discusses how poverty estimates can be enhanced by integrating household surveys and censuses with data extracted from satellite imagery. As part of a special ADB knowledge initiative, computer vision techniques and machine-learning algorithms were applied on datasets from the Philippines and Thailand to demonstrate increased granularity of poverty estimation using artificial intelligence. The report identifies practical considerations and technical requirements for this novel approach to mapping the spatial distribution of poverty. It also outlines the investments required by national statistics offices to fully capitalize on the benefits of incorporating innovative data sources into conventional work programs.
Author: Miao, Fengchun
Publisher: UNESCO Publishing
ISBN: 9231004476
Category : Political Science
Languages : en
Pages : 50
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Book Description
Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]
Author: Asian Development Bank
Publisher: Asian Development Bank
ISBN: 9292621327
Category : Business & Economics
Languages : en
Pages : 159
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Book Description
The “leave no one behind” principle of the 2030 Agenda for Sustainable Development requires appropriate indicators for different segments of a country’s population. This entails detailed, granular data on population groups that extend beyond national trends and averages. The Asian Development Bank, in collaboration with the Philippine Statistics Authority and the World Data Lab, conducted a feasibility study to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics in the Philippines. This report documents the results of the study, which capitalized on satellite imagery, geospatial data, and powerful machine learning algorithms to augment conventional data collection and sample survey techniques.
Author: Virginia Eubanks
Publisher: St. Martin's Press
ISBN: 1466885963
Category : Social Science
Languages : en
Pages : 273
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Book Description
WINNER: The 2019 Lillian Smith Book Award, 2018 McGannon Center Book Prize, and shortlisted for the Goddard Riverside Stephan Russo Book Prize for Social Justice Astra Taylor, author of The People's Platform: "The single most important book about technology you will read this year." Dorothy Roberts, author of Killing the Black Body: "A must-read." A powerful investigative look at data-based discrimination?and how technology affects civil and human rights and economic equity The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years—because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely.
Author: Shawn Cole
Publisher: Abdul Latif Jameel Poverty Action Lab
ISBN: 9781736021606
Category :
Languages : en
Pages : 618
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Book Description
This Handbook intends to inform Data Providers and researchers on how to provide privacy-protected access to, handle, and analyze administrative data, and to link them with existing resources, such as a database of data use agreements (DUA) and templates. Available publicly, the Handbook will provide guidance on data access requirements and procedures, data privacy, data security, property rights, regulations for public data use, data architecture, data use and storage, cost structure and recovery, ethics and privacy-protection, making data accessible for research, and dissemination for restricted access use. The knowledge base will serve as a resource for all researchers looking to work with administrative data and for Data Providers looking to make such data available.
Author: Keith D. Harries
Publisher:
ISBN:
Category : Cartography
Languages : en
Pages : 220
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Book Description
Author: Johnny Saldana
Publisher: SAGE
ISBN: 1446200124
Category : Reference
Languages : en
Pages : 282
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Book Description
The Coding Manual for Qualitative Researchers is unique in providing, in one volume, an in-depth guide to each of the multiple approaches available for coding qualitative data. In total, 29 different approaches to coding are covered, ranging in complexity from beginner to advanced level and covering the full range of types of qualitative data from interview transcripts to field notes. For each approach profiled, Johnny Saldaña discusses the method’s origins in the professional literature, a description of the method, recommendations for practical applications, and a clearly illustrated example.
