THE TIME-TO-BUILD TRADITION ♣ IN BUSINESS CYCLE
Bibliographic record
Abstract
♣ Prepared in homage to celebrate the eightieth anniversary of the publication of Tinbergen's path-breaking Ein Schiffbauzyklus and the sixtieth anniversary of the publication of Goodwin's Nonlinear Accelerator and the Persistence of Business Cycles. ♥ The second author had the pleasure and privilege of direct and indirect instruction and years of inspiration on the matters dealth with in this paper by some of the pioneers of the relevant theory. In particular, of course, Richard Goodwin and Björn Thalberg, but also Trygve Haavelmo, Nicholas Kaldor and, especially, Jan Tinbergen (alas only very late in his noble life; see footnote 1, in the main text). Stefano Zambelli's influence, via innumerable discussions with the second author for over a quarter of a century, and through his important written works on Frisch and Kalecki, is pervasive. He is, however, not responsible for any remaining infelicities in this paper.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".