Poverty Measurement with Ordinal Data
Bibliographic record
Abstract
The Foster, Greer, Thorbecke (1984) class nests several of the most widely used mea- sures in theoretical and empirical work on economic poverty. Use of this general class of measures, however, presupposes a dimension of well-being that, like income, is cardinally measurable. Responding to recent interest in dimensions of well-being where achievements are recorded on an ordinal scale, this paper develops counterparts to the popular FGT measures that are still meaningful when applied to ordinal data. The resulting ordinal FGT measures retain the simplicity of the classical FGT measures and also many of their desirable features, including additive decomposability. This paper also develops ordinal analogues of the core axioms from the literature on economic poverty, and demonstrates that the ordinal FGT measures indeed satisfy these core axioms. Moreover, new domi- nance conditions, which allow for poverty rankings that are robust with respect to the choice of poverty line, are established. Lastly, the ordinal FGT measures are illustrated using self-reported data on health status in Canada and the United States.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".