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
In part II, alternating episodes of poor and superior performance were traced to structural change endogenous to the performance of the economy, forming a causal chain linking successive episodes via negative feedback effects. The structural changes linking the episodes differed, with technology developments providing the link between the period of industrialization and the 1930s, and institutional developments constituting the links between the 1930s and the golden age and subsequently between the golden age and the existing age of high unemployment. Having made a point of the differences in linkages, we have no hesitation in stating that the failure to recover quickly once an adverse structural change has occurred is a failure of institutions to adapt to changing circumstances. As discussed in chapter 8, the depressed economic conditions extending over most of the 1930s could have been ended earlier with a Keynesian deficit spending programme, had there been the political will to introduce it. Although the cause of the Great Depression was technology, recovery was prevented by an institutional constraint on stimulative AD policy. In chapter 11 we argued that the golden age was brought to an end by the eventual incompatibility of full employment and acceptable rates of inflation. The institutional requirements for a full employment recovery today are more demanding than in the 1930s.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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