Bibliographic record
Abstract
This paper uses an ex-post partial-equilibrium framework to measure the impact of marginal changes in industrial pollution abatement costs on the u.s . balance of trade in general, and balance of trade with Canada in particular. The impacts are found to be negative for most industries, growing with trade volume, and small relative to domestic consumption. In addition, some evidence is found that pollution control programs have changed the u.s . comparative advantage such that more high-abatement-cost goods are imported and more low-abatement-cost goods are exported. La réduction de la pollution industrielle: l’impact sur la balance commerciale . Ce mémoire utilise un cadre d’analyse d’équilibre partiel ex-post pour calibrer l’impact de changements à la marge dans les coûts de la réduction de la pollution industrielle sur la balance commerciale des Etats-Unis et en particulier sur la balance commerciale avec le Canada. Il appert que les impacts sont négatifs pour la plupart des industries, qu’ils croissent avec la taille des flux commerciaux, et qu’ils sont petits relativement à la consommation domestique. De plus, il semble que les programmes de lutte à la pollution ont transformé l’avantage comparatif des Etats-Unis de telle manière qu’on importe davantage de biens pour lesquels les coûts de réduction de la pollution sont élevés et qu’on exporte davantage de biens pour lesquels ces coûts sont bas.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".