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
Using consumer price indexes from cities in the U.S., Canada and Mexico, we estimate the "border effect" on U.S.-Mexican relative prices and find that it is nearly an order of magnitude larger than for U.S.-Canadian prices. However, during a very stable sub-period in Mexico (May 1988 to November 1994), the "width" of the U.S.-Mexican border falls dramatically and becomes approximately equal to the U.S.-Canadian border. We then show that when consideration is limited to cities lying geographically very close to the U.S.-Mexican border--San Diego, Los Angeles, Houston, Dallas, Tijuana, Mexicali, Juarez, and Matamoros--the border width falls compared to that estimated with the full sample of U.S. and Mexican cities, but falls only very slightly. We also present evidence that the border effect in U.S.-Mexican prices is not primarily due to the border effect in U.S.-Mexican wages. Finally, using the prices of 276 highly dis-aggregated goods and services, we estimate the variability of relative prices of different items within Mexican cities. This measure of relative price variability declines during the stable peso sub-period, but by less than the decline in nominal and real (i.e., CPI-based) exchange rate variability. Our results are strong evidence of a "nominal border effect" in relative prices within NAFTA, but also indicate that real side influences are important.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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