Hysteresis and non-linearities in unemployment rates
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
This study tests whether there is evidence of mean reversion in unemployment rates using the recently developed unit root test of Kapetanios et al. (2003 Kapetanios, G, Shin, Y and Snell, A. 2003. Testing for a unit root in the nonlinear STAR framework. Journal of Econometrics, 112: 359–79. [Crossref], [Web of Science ®] , [Google Scholar]). In this framework, the null hypothesis of a unit root process is tested against the alternative of a globally stationary exponential smooth transition autoregressive process. Applying the test to monthly data for Australia, Canada, Finland, Sweden and the USA, it is concluded that unemployment hysteresis finds less support when non-linearities are allowed for compared to the benchmark of using a standard Augmented Dickey–Fuller test.
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 | 0.000 | 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