Reproducible materials for 'The Boomer Penalty: Excess Mortality among Baby Boomers in Canada and the United States'
Bibliographic record
Abstract
Studies suggest that baby boomers in Canada and the United States have experienced a slowdown, or even deterioration, in the all-cause mortality improvements relative to neighboring cohorts. These findings are counterintuitive and surprising. According to the technophysio evolution theory, the unprecedented improvements in early life conditions experienced by baby boomers should have led to declines in morbidity and mortality in later life, as was the case for generations born earlier. The present study explores mechanisms that could have produced the excess mortality for the baby boom cohorts in Canada and in three racial/ethnic groups in the United States. Using micro-level mortality data from vital statistics systems, we analyzed the contribution of causes of death that are likely driving this cohort’s excess mortality and their dynamic over time. The analyses are done using demographic decomposition, visual, and statistical methods. We found evidence of a higher susceptibility of the trailing edge boomers to behavioral causes of death, namely mortality from drugs, alcohol, HIV/AIDS, hepatitis C, COPD, and suicides. Most of these causes contributed to the all-cause mortality disadvantage of boomers by sustained cohort effects that escorted the cohorts over time. This invites a rethinking of the mechanisms driving current age-period-cohort mortality patterns. Mechanisms that can generate the observed cohort disadvantage, such as more prevalent levels of distress and frustration among boomers –the birth cohort effect proposed by Easterlin–, and the riskier attitudes toward drug use and sexual practices that are constituent of the boomer generation identity are addressed and discussed. https://www.demogr.mpg.de/en/publications_databases_6118/publications_1904/mpidr_working_papers/the_boomer_penalty_excess_mortality_among_baby_boomers_in_canada_and_the_united_states_6387/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.074 | 0.006 |
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; both teacher heads agree on what is shown here.
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".