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 We review recent advances in dynamic stochastic general equilibrium theory concerned with the emergence of fat‐tailed time‐series distributions. Focusing on mechanisms that are firmly grounded in structural equilibrium models, we provide a common reference framework to organize existing contributions according to whether they entail extreme business cycle swings as an endogenous response to small and short‐lived shocks ( “thin in, fat out” ), or rather as an automatic consequence of large and/or heteroskedastic exogenous impulses ( “fat in, fat out” ). Within the former class, non‐Gaussian features of equilibrium patterns can endogenously emerge in fully rational, Gaussian environments. Using an empirically plausible real business cycle framework, we also report novel simulation‐based evidence that helps reconcile theoretical predictions with the documented higher‐order properties of time‐series data for output measures.
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.
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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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