Skilled–unskilled wage inequality and imitation in a product variety model: A theoretical analysis
Why this work is in the frame
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Bibliographic record
Abstract
The article develops a dynamic three-sector product variety model to analyze the role of imitation on skilled–unskilled wage inequality. One of these sectors produces varieties of innovated products with skilled labor as well as unskilled labor and another sector produces varieties of imitated products with only unskilled labor. Also, there is an R&D sector developing blueprints of new products with skilled labor as the only input. However, imitation is costless. It is shown that an increase in skilled (unskilled) labor endowment raises (lowers) the rate of growth, raises (lowers) the skilled–unskilled wage ratio, and lowers (raises) the level of social welfare. However, an increase in the rate of imitation raises this growth rate, lowers the skilled–unskilled wage ratio, and raises the level of social welfare.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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