Growing up in a growing economy. Reassessing changes in biological living standards in Portugal during the twentieth century
Bibliographic record
Abstract
This paper explores the assumptions about sample representativeness and provides a re-analysis of the data utilized by Cermeño and co-workers (2023a) to examine changes in the biological standards of living in Portugal over the 20 th century, from records of child height taken from the Hospital de São Roque (1945-2000) in Lisbon, Portugal. The authors suggest that the largest decline in the prevalence of stunting – and concomitantly, the greatest increase in biological standards of living or population well-being - occurred during the Estado Novo dictatorship, before the democratic transition of 1974. Our analysis relies on the original raw data and results, as well re-calculated prevalences of stunting, examination of heigh-for-age distributions, and it also relied on other growth studies for comparison and various historic documents and published sources to assess the representatives of the sample. The Hospital de São Roque data may not fully represent the population of Lisbon, or Portugal more broadly, suggesting some caution is needed when using them to examine changes in growth patterns over time. Results indicate that the most significant decline in stunting - reflecting the greatest improvement in the standard of living - occurred after, not before, the democratic transition of 1974. • Cermeño and co-workers (2023) suggest that a dictatorship is the main driver for improvement in living standards • Child height and weight data from a pediatric hospital data can be problematic and controversial • A detailed examination of sample representativeness and a re-analysis of data is carried out • The hospital sample is comprised of the poorest and sickest, and its composition and nature changes significantly over time • The current study confirms greater increase in living standards during the democratic regime • Additional observations suggest dictatorship may have caused depression in living standards
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".