Progress Stalled? The Uncertain Future of Mortality in High‐Income Countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Steady and significant improvements in life expectancy have been a bright spot for human progress for the last century or more. Recently, this success has shown signs of faltering in some high‐income countries, where mortality improvements have slowed or even reversed since the early 2010s. Combined with the large mortality shock of the COVID‐19 pandemic, guaranteed forward progress feels less certain. We review mortality trends in high‐income countries since 2000 through the COVID‐19 pandemic. While deteriorating mortality in the United States has received the most attention, countries including the United Kingdom, Canada, the Netherlands, Greece, and Germany are also seeing slowdowns. Before COVID‐19, these slowdowns largely reflected stalling improvements in cardiovascular disease mortality and increases in deaths from external causes in young and midlife for the worst‐performing countries. We discuss prospects for the future of mortality in high‐income countries, including lingering impacts of the COVID‐19 pandemic, challenges and opportunities related to the obesity epidemic, and emerging reasons for both optimism and pessimism. While biological limits to increased life expectancy may eventually dominate long‐term trends, human‐made social factors are currently holding many countries back from already achievable best‐practice life expectancy and will be key to near‐term improvements.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 it