Bibliographic record
Abstract
This paper theoretically investigates how trade affects skill intensity at firm level. In order to analyze this, we develop a model in which firms engages in the division of labor within firms by in putting two types of labor. Unskilled labor is inputted into the production line of the production division and skilled labor is inputted into the production division to conduct the production line. Firms can reduce marginal cost by promoting the division of labor in the production division. Both types of labor are also inputted into head office for domestic market and for export market. These head offices are different in skill intensity. Though all firms are ex-ante identical, the division of labor of exporters is stronger than that of non-exporters on the unique equilibrium. That fixed labor input of headquarter division for export market is more skill intensive than that for domestic market is equivalent to the fact that total labor input of exporters is more skilled intensive than that of non-exporters. Furthermore, all firms reduce the type of labor inputted intensively into head quarter division for the export market while raising the type of labor inputted less intensively into that division.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".