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Record W6938809375 · doi:10.6068/dp168a6569e9292

TREND: World Bank. Climate Change Data [Archive]: National Resilience | Country: Afghanistan, Albania, Algeria, American Samoa, Angola, Antigua and Barbuda, Argentina, Armenia, Aruba, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burma, Burundi, Cambodia, Cameroon, Canada, Cape Verde, Cayman Islands, Central African Republic, Chile, China, Colombia, Comoros, Congo (Brazzaville), Cook Islands, Costa Rica, Cote D'Ivoire, Croatia, Cuba, Cyprus, Czech Republic, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Ethiopia, Federated States of Micronesia, Fiji, Finland, France, French Polynesia, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guam, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hong Kong, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Korea, North, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Macau, Macedonia, Madagascar, Malaysia, Malawi, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Moldova, Monaco, Mongolia, Morocco, Myanmar, Mozambique, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Niue, Northern Mariana Islands, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Puerto Rico, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Korea, Spain, Sri Lanka, Sudan, Suriname, Swaziland, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Turks and Caicos Islands | Socioeconomic Indicator: Access to improved sanitation, Access to improved water source, Cereal yield, Access to electricity, Paved roads, Physicians, Disaster risk reduction progress score, Public sector mgmt & institutions avg., Ease of doing business, 1990 - 2008. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 051-005-003

2019· other· en· W6938809375 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeGreenhouse gasPsychological resiliencePopulationResilience (materials science)Gross domestic productClimate resilienceGlobal warmingWorld population

Abstract

fetched live from OpenAlex

datasets.shared.infosheet.CitationMgr@2605 Dataset: Presents statistics on the capacity of human systems to cope with the impacts of climate change, such as economic capacity, institutional capacity, and extent of public infrastructure. The data are sourced by the World Bank from national and international organizations, including the International Energy Agency, World Health Organization, United Nations Children's Fund, and International Road Federation. The World Bank Climate Change Database present statistics that relate to climate change, development, and the relationship between the two. The over 70 indicators included in the dataset are grouped into four areas: Size of the Economy, which presents data on population size and Gross Domestic Product (GDP); Exposure to Impacts, which provides data that suggest the degree to which a country or region may be exposed to changes in the prevailing climate and natural environment, with potential impacts on human health, food security, water supply, and physical infrastructure; Resilience, which includes data on the capacity of human systems to cope with the impacts of climate change, such as economic capacity, institutional capacity, and extent of public infrastructure; GHG Emissions and Energy Use, which includes data on the emissions of greenhouse gases (GHG) and energy use, including measures of energy efficiency and carbon intensity of economy. Data are shown for economies with populations greater than 30,000 or for smaller economies if they are members of the World Bank. Where available, data are provided for all countries and by nation covering the period 1990-2011. http://data.worldbank.org/topic/climate-change Category: Population and Income, Natural Resources and Environment Subject: Climate Change, Economic Development, Social Development, Health Care Access Source: World Bank Founded in 1944 as a result of the Bretton Woods Conference, the World Bank is an independent specialized agency of the United Nations that provides financial and technical assistance to developing countries in order to foster economic growth and reduce poverty. Today, the World Bank Group comprises five institutions owned by 187 member countries: the International Bank for Reconstruction and Development (IBRD), which focuses on middle-income and creditworthy poor countries; the International Development Association (IDA), which focuses on least developed countries; the International Finance Corporation (IFC); the Multilateral Guarantee Agency (MIGA); and the International Centre for the Settlement of Investment Disputes (ICSID). http://www.worldbank.org/

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.866
Threshold uncertainty score0.435

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.025
Science and technology studies0.0010.000
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1300.092

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.251
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes1
Has abstractyes

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