Bibliographic record
Abstract
Mexico represents the third largest trading partner with the United States after China and Canada, yet the retail apparel industry has not embraced Mexico as a preferred sourcing partner. Imports from China and Southeast Asia far outweigh imports from Mexico in terms of the retail staples of apparel, footwear, and accessories. Mexico, however, is increasingly becoming an ideal venue for U.S. retail sourcing as Chinese wages and inflation rise. Mexico has become cost competitive with China and it is much more conveniently located. In this honors thesis, I explore Mexico as a sourcing partner for the apparel and footwear industries. I also explore Mexican logistics and transportation and the opportunities for our local Tucson, Arizona community to become a major inland port for future Mexican imports. I review why apparel retailers have not yet embraced Mexico, and the catalysts required for apparel retailers to transfer more sourcing opportunities to Mexico. Finally, I challenge both perceived and real obstacles to Mexican manufacturing and sourcing and conclude that Mexico will emerge as a dominant partner to the U.S. retail industry within the next generation.
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".