Bibliographic record
Abstract
In this paper, I ask the question: <it>Does the output-mix of countries change in response to changes in factor endowments?</it> If so: <it>How long does it take?</it> Using data on capital, as well as skilled and unskilled labour employed in three-digit International Standard Industrial Classification (ISIC) manufacturing industries for a sample of 27 developing and developed countries over the 1973–1990 period, I find that the output-mix of countries does not change in response to endowment changes, even after 15 years. This answer raises another question: <it>How then do countries absorb changes in factor endowments?</it> The data show that in both the short and long runs, an increase in the supply of a production factor reduces its rate of return and makes it more intensively used in all sectors of the economy: changes in production techniques. In the long run, the point estimate is that the reduction in the rate of return is more than 50% larger than in the short run. This is consistent with induced innovations being predominantly biased towards the scarce factor.
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.
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) | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".