Bibliographic record
Abstract
In the period 1974-1990 Argentina´s income per capita fell by 25%. A Solow growth decomposition shows that at most one quarter of this fall can be explained by a reduction in the capital/labor ratio. A study of labor reallocation shows that between 1973 and 1993 employment expanded the most in sectors with a declining output per worker and this reallocation of labor explains 44% of the fall in output per worker. We argue that policies that increase the cost of capital may explain these observations. Consider a two sector model where capital/labor substitution is low in the tradable goods sector and high in the non-traded goods one. If the steady state capital stocks falls, labor .ows from the tradable goods sector to the non-traded goods one, leading to a reduction in income per capita, productivity and wages. Thus, policies that increase the cost of capital have a direct e.ect on output through the fall in the capital stock and an indirect e.ect that operates through a reallocation of labor induced by the fall in investment.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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; both teacher heads agree on what is shown here.
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".