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 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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".