Vocational Education in the Americas: Comparing the Secondary Education Systems of Canada, Mexico, and the United States
Bibliographic record
Abstract
Mexico, the United States, and Canada share a rich history of trade, migration, and cultural exchange. This chapter examines each country’s national education system, focusing specifically on vocational career paths in upper secondary education, and reviews the economic, demographic, and political factors influencing each country’s educational needs and priorities. Using systems theory as a framework, each national system is divided into inputs, processes, and outputs to evaluate and compare their effectiveness. The inputs of each country include its educational goals and its level of investment in the education system. Mexico’s goals emphasize life skills, the United States focuses on workforce preparation, and Canada, lacking national education oversight, is examined through the goals of several provinces. The processes within each Upper Secondary Education (USE) system are analyzed by comparing the structures and approach to vocational education in each country. Ontario, the largest Canadian province, offers a Specialist High Skills Major; Mexico has implemented a nationwide dual education model; and in the United States, an example from Texas illustrates its work-based learning program. The outputs include education outcomes measured by OECD’s PISA assessments and an overview of each country’s policy approach to achieving its educational goals. Canada’s schools perform the best, while Mexico’s lag significantly. This study found that despite differences in their USE systems, each country has aligned policy initiatives with its own education goals, designed to meet each country’s specific national needs.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".