The Production of Credentialized Aspirations: Familial Strategies in Mexican Upper‐Middle‐Class International Mobility
Bibliographic record
Abstract
ABSTRACT This paper examines how Mexico's upper‐middle classes construct credentialized aspirations —intergenerational, place‐based strategies of class reproduction centered on the pursuit of globally recognized educational and professional credentials. Drawing on 45 life‐history interviews with Mexican professionals in Vancouver and Seattle and their parents in Monterrey, the study situates these strategies within the broader context of North American economic integration since NAFTA. Rather than engaging in family migration projects, upper‐middle‐class families invest in elite international education to cultivate cosmopolitan dispositions and transnational networks from an early age, enabling their children to navigate ‘highly skilled’ migration regimes in the United States and Canada. I develop the concept of credentialized aspirations to describe how the iterative accumulation of credentials—degrees, language proficiency, and professional experience—functions as a mechanism for sustaining social mobility under conditions of neoliberal uncertainty. This analysis reveals how regional integration, private education infrastructures, and meritocratic migration policies intersect to shape the geographies of privilege and mobility in North America. By foregrounding the Mexican case, the paper advances population geography scholarship on aspirations and mobility, demonstrating how elite reproduction operates through localized practices that are deeply entwined with transnational imaginaries of success.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 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".