Entanglements: Volkswagen de MĂŠxico and Global Capitalism
Bibliographic record
Abstract
This dissertation is an ethnographic study of global capitalism. It examines the multilayered presence of Volkswagen de México to grapple with the double-edged sword of transnational economic dependencies. Car manufacturing in Mexico has created jobs for a number of college graduates, middle class status, modes of relationality and care, and even the possibility to migrate to Germany. At the same time global car production relies on a large number of low-wage and uncertain jobs, on mechanisms that make labor cheap and discipline the labor force, as well as on land and water dispossession. While Volkswagen de México is a medium of inclusivity into 21st century global capitalism, it has also created contentious relations on the ground: among those who celebrate the presence of the factory, those who oppose it, those who have been violently excluded, and among unionized and non-unionized workers. To elucidate this complex and convoluted landscape of social relations, this study examines how transnational car production intersects with processes of nation-state formation, local ideas about status, and personal aspirations, as well as the conjunctures between global transformations, manufacturing, and the North American Free Trade Agreement. This dissertation shows how Volkswagen’s car economy has endured through forms of domination, subjugation and accommodation, and traces its not-always-predictable effects on the ground. Thereby it offers a nuanced and textured account of how global capitalism is constituted trans-locally.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".