The effects of prenatal deaths on national life expectancy: case study U.S.A.
Bibliographic record
Abstract
Introduction: It is a positive indicator that human lifeexpectancies calculated from birth have been increasing. The current standards for counting life-years, however, assume social desirability and exclude all prenatal deaths. These assumptions mask low life-year deaths and obscure results of medical and environmental interventions, thus falsely indicating higher life expectancies.Aim: To quantify the life expectancy with and withoutsocial desirability.Methods: This case study investigates 1930 to 2016 using CDC and World Bank data for the U.S. for the impact of social desirability on life expectancy.Results: It is evident, published U.S. life expectancies are greatly exaggerated and what would have beenshort-lived Americans are disproportionately labeled as socially-undesirable and ignored when counting life years, thus presenting an overly-optimistic view of U.S. health.Conclusions: A comprehensive global investigation isneeded, and a refinement of life expectancy calculationsshould be introduced, which does not bias results by only counting life expectancy from the time of live birth.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".