Income Distribution and Social Exclusion of Children: Evidence from Italy and Spain in the 1990s
Bibliographic record
Abstract
Income poverty rates are often used as indicators of the level of deprivation of populations and as measures of the relative position of sub-groups within populations. In this paper, we examine the links between monetary and non-monetary indicators of deprivation and social exclusion. We focus on children since they constitute one of the most vulnerable demographic groups in many countries. Understanding the poverty level and social exclusion of children is important not only in its own right but also because there is concem that the deprivation condition is transmitted from one generation to the next. Italy and Spain are two European countries that stand out for the high social risks faced by households with children. The welfare states of these two countries have put minimal effort in protecting these population groups. Our results strongly confirm the view that the use of non-monetary indicators enriches the analysis of well-being. It is indeed the case that the two countries, which perform very similarly in many aspects, show very diverse levels of deprivation and social exclusion once non-monetary indicators are used. In particular, Italy and Spain are characterized by substantial disparities in all the domains analyzed except for the domain of income poverty.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".