Multidimensional Poverty in Bhutan: Estimates and Policy Implications
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".