Beyond Headcount: Measures that Reflect the Breadth and Components of Child Poverty
Bibliographic record
Abstract
This paper presents a new approach to child poverty measurement components of child poverty. The Alkire and Foster method presented in this paper seeks to answer the question 'who is poor' by considering the intensity of each as poor, the measures aggregate information on poor down to see where and how children taking into account the breadth, depth or severity of dimensions of child poverty. one way to apply this method to child poverty measurement of the Demographic Health Survey the AF adjusted headcount ratio headcount, because it also reflects the simultaneous deprivations children experience (intensity) this, we argue that child poverty should not be assessed only according to the incidence of poverty but also by the intensity of deprivations that batter poor children's lives at the same time. example is used to illustrate how to measure can be broken down by groups and by dimensions in order to interpret changes over time, and how to undertake robustness checks concerning the poverty cut
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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 | 0.002 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".