Bibliographic record
Abstract
Abstract The impact of macroeconomic fluctuations on health and mortality rates has been a highly studied topic in the field of economics. Many studies, using fixed-effects models, find that mortality is procyclical in many countries, such as the United States, Germany, Spain, France, Pacific-Asian nations, Mexico, and Canada. On the other hand, a small number of studies find that mortality decreases during economic expansion. Differences in the social insurance systems and labor market institutions across countries may explain some of the disparities found in the literature. Studies examining the effects of more recent recessions are less conclusive, finding mortality to be less procyclical, or even countercyclical. This new finding could be explained by changes over time in the mechanisms behind the association between business cycle conditions and mortality. A related strand of the literature has focused on understanding the effect of economic fluctuations on infant health at birth and/or child mortality. While infant mortality is found to be procyclical in countries like the United States and Spain, the opposite is found in developing countries. Even though the association between business cycle conditions and mortality has been extensively documented, a much stronger effort is needed to understand the mechanisms behind the relationship between business cycle conditions and health. Many studies have examined the association between macroeconomic fluctuations and smoking, drinking, weight disorders, eating habits, and physical activity, although results are rather mixed. The only well-established finding is that mental health deteriorates during economic slowdowns. An important challenge is the fact that the comparison of the main results across studies proves to be complicated due to the variety of empirical methods and time spans used. Furthermore, estimates have been found to be sensitive to the use of different levels of geographic aggregation, model specifications, and proxies of macroeconomic fluctuations.
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 | 0.004 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".