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Record W2107300937

Multidimensional Poverty in Bhutan: Estimates and Policy Implications

2008· preprint· en· W2107300937 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2008
Typepreprint
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsnot available
FundersAustralian Agency for International DevelopmentInternational Development Research CentreGovernment of CanadaDepartment for International DevelopmentUnited States Agency for International Development
KeywordsPovertyRural areaSurvey data collectionGeographyWeightingEconomicsStandard of livingSocioeconomicsEconomic growthDevelopment economicsStatisticsPolitical scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

<p>This paper estimates multidimensional poverty in Bhutan applying the methodology developed by Alkire and Foster using the 2007 Bhutan Living Standard Survey data. Five dimensions are considered for estimations in both rural and urban areas: income, education, room availability, access to electricity and access to drinking water, and two additional dimensions are considered for estimates in rural areas only: access to roads and land ownership. It is found that multidimensional poverty is mainly a rural phenomenon, although urban areas present non-depreciable levels of deprivation in room availability and education. Within rural areas, weighting each indicator equally, deprivation in electricity, education room and income are the highest and similar in contribution to aggregate multidimensional poverty. When weights derived from the Gross National Happiness Survey are used, income deprivation significantly increases its contribution as it receives a higher weight. Rankings of districts by their poverty estimate are found to be robust for a wide range of poverty cutoffs. The methodology is suggested as a potential formula for national poverty measurement as well as a tool for budget allocation.</p>

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0030.004
Scholarly communication0.0000.001
Open science0.0020.004
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.330
Teacher spread0.276 · 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