North American Trade Policy for Agriculture and Forestry: Can Economics Trump Politics?
Bibliographic record
Abstract
Despite overwhelming evidence of benefits overall from lower barriers to trade in goods and services, the number of trade restrictions continues to grow. In some nations, nationalistic politicians who threaten to build walls between nations and reject both new and established trade treaties have gained considerable public support by fanning the resentment and anger of those left behind in a globalizing world. Trade and immigration have incorrectly been blamed. Instead, it should be recognized that economic growth has been fueled by technological and institutional changes that have been accelerated by trade and investment. While these changes improve standards of living overall and create new job opportunities, they also displace workers in high cost regions and industries. Perceptions of the fairness of distribution of gains from trade are likely to be improved where public policy effectively assists labor adjustment and mandates socially acceptable employment standards and safety nets. Possible ways to encourage improvements in communication of the benefits of growth that arise from trade and globalization are suggested. Malgré des preuves accablantes démontrant les avantages généraux provenant de la réduction des barrières au commerce de biens et services, le nombre de ces restrictions continue d'augmenter. Certaines nations oú des politiciens nationalistes menacent la construction de murs frontaliers et rejettent les accords de commerce, autant nouveaux que déjà en vigueur, reçoivent un soutien public considérable en encourageant l'animosité et la colère de ceux qui se sentent exclus de la mondialisation. Le commerce et l'immigration portent sans raison le blâme. Il faut plutôt reconnaître la croissance économique nourrie par les changements technologiques et institutionnels, ces derniers accélérés par le commerce et l'investissement. Alors que ces changements améliorent, en général, les niveaux de vie et créent de nouvelles possibilités d'emplois, ils délogent aussi les travailleurs au sein d'industries à coût élevé. La perception de justice dans la répartition des gains de commerce pourrait s'améliorer là où les politiques publiques appuient efficacement les ajustements à la main‐d'œuvre et mandatent des normes de travail et des dispositions de soutien acceptables pour la société. L'article propose des moyens pour encourager des améliorations à la communication des avantages de la croissance provoquée par le commerce et la mondialisation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".