The role of multinationals in the host country: Spillover effects from the presence of auto car makers in Mexico
Bibliographic record
Abstract
Multinational Companies (mnes) have a long presence in the automobile industry in Mexico, since 1925. The North America free trade agreement (nafta) has promoted this foreign-owned industry to develop the locally owned auto supplier industry. In this study, we focus on two analyses: in the fi rst one, the “Double Diamond” model is used to examine the sources of competitiveness of the auto industry, the auto suppliers, and the possible spillover effects on fi rst and second tier suppliers. In the second one, we focus on a local case by analyzing the cluster located in Puebla to see the relations between the Original Equipment Manufacturer Volkswagen (oem vw) and its suppliers. Our fi ndings indicate that the foreign-owned auto industry in Mexico has been successful in terms of gaining world’s export market share within the period 1993-2003 and that mnes have promoted the competitiveness of some existing locally owned suppliers through collaborative agreements and joint ventures. The local case of the Puebla cluster reveals that some local, in its majority foreign-owned, auto suppliers have been certifi ed and integrated as tier 1 suppliers of the oem vw, but there is not enough evidence that tier 2 and 3 locally owned suppliers have been fully integrated into the supply chain.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".