<i>International Trade and Political Conflict: Commerce, Coalitions, and Mobility</i>. By Michael J Hiscox. Princeton, NJ, and Oxford: Princeton University Press, 2002. Pp xiv, 209. $49.50, cloth; $18.95, paper.
Bibliographic record
Abstract
This short book has a novel thesis, which is that the degree of factor mobility at the national level influenced the politics of foreign-trade policies. When factor mobility was high, tariff legislation was class legislation. When mobility was low, tariffs were decided by interest-group competition. Michael Hiscox brings data on mobility to bear on the history of foreign trade policies of the six countries—the United States, Britain, France, Sweden, Canada, and Australia—over the last one or two hundred years or so, devoting a chapter to each. He then tests his ideas quantitatively on U.S. congressional voting between 1924 and 1994, finding that, when the indicators of factor mobility were low, an “interest group theory” better explains U.S. tariff politics than does a “class legislation theory” (and the reverse when mobility was high).
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".