US employment exposure to domestic and foreign tariff changes under <scp>NAFTA</scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Literature examining the effects of changes in trade agreements and import competition on US employment and wages has focused primarily on non‐agricultural industries and changes in US import tariffs. We propose a method for measuring worker exposure to changes in agricultural tariffs using a newly developed county‐level dataset of employment shares by crop and livestock type. We apply the method to examine the spatial concentration of US county‐level employment‐weighted exposure to changes in tariffs caused by the North American Free Trade Agreement (NAFTA). Results reveal noteworthy decreases in average US county‐level crop and livestock employment exposure to Mexican import tariffs on US products. Findings also show spatial variation in US employment exposure to changes in Mexican import tariffs on US agricultural and non‐agricultural goods. Changes in county‐level employment exposure to US and Canadian import tariffs after NAFTA implementation are relatively minor given low initial tariff rates prior to the agreement.
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.
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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 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 it