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Where do the World's Multidimensionally Poor People Live?

2013· report· en· W2166693703 on OpenAlexfundaboutno aff
Sabina Alkire, José Manuel Roche, Andy Sumner

Bibliographic record

VenueUniversity of Oxford · 2013
Typereport
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsnot available
FundersBundesministerium für Wirtschaftliche Zusammenarbeit und EntwicklungAustralian Agency for International DevelopmentGeorg-August-Universität GöttingenUniversity of OxfordInternational Development Research CentreEconomic and Social Research CouncilInternational Fine Particle Research InstituteUnited Nations Development ProgrammeRobertson FoundationUNICEF
KeywordsPovertyDistribution (mathematics)Quarter (Canadian coin)Developing countrySocioeconomicsPsychologyGeographyDemographic economicsEconomic growthEconomicsMathematics

Abstract

fetched live from OpenAlex

This paper asks where do the world's multidimensionally poor people live? The paper considers how the global distribution of multidimensional poverty differs from the global distribution of income poverty and assesses the sensitivity of findings to widely used (although somewhat arbitrary) country classifications. Surprisingly perhaps, only a quarter of multidimensionally poor people and just one-third of severely multidimensionally poor people live in the world's poorest countries -meaning Low Income Countries (LICs) or Least Developed Countries (LDCs). The sensitivity of findings about country thresholds for low and middle-income countries is discussed. The paper argues that there is a split of distribution poverty between both stable Middle-Income Countries (MICs) and low-income fragile states and that there is a 'multidimensional bottom billion' living in stable MICs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.148
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.030
GPT teacher head0.276
Teacher spread0.246 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations15
Published2013
Admission routes2
Has abstractyes

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