Bibliographic record
Abstract
The authors study the empirical, \n cross-country relationship between macroeconomic volatility \n and long-run economic growth. They address four central \n questions: 1) Does the volatility-growth link depend on \n country and policy characteristics, such as the level of \n development or trade openness? 2) Does this link reflect a \n statistically and economically significant causal effect \n from volatility to growth? 3) Has this relationship been \n stable over time and has it become stronger in recent \n decades? 4) Does the volatility-growth connection actually \n reveal the impact of crises rather than the overall effect \n of cyclical fluctuations? The authors find that \n macroeconomic volatility, and long-run economic growth are \n indeed negatively related. This negative link is exacerbated \n in countries that are poor, institutionally underdeveloped, \n undergoing intermediate stages of financial development, or \n unable to conduct counter-cyclical fiscal policies. They \n find evidence that this negative relationship actually \n reflects the harmful effect from volatility to growth. \n Furthermore, the authors find that the negative effect of \n volatility on growth has become considerably larger in the \n past two decades, and that it is mostly due to large \n recessions rather than normal cyclical fluctuations.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".