Comparative Education Understanding Why the United States Underperforms in International Test Scores: Learning From China, Japan, Canada, and the United Kingdom
Bibliographic record
Abstract
The United States has slow but surely fallen in their standing in global education. Education affects everything from economic standing to innovation for the future and thus the decline in educational standing presents a problem for the U.S. This research uses the Organization for Economic Co-Operation and Development’s Programme for International Student Assessment as a baseline for where countries place relative to the United States. The study then uses Canada and England to represent nations with ideologies and economies most similar to the United States as well as China and Japan to represent countries that differ. Each nation’s governmental structure, societal issues, and economies are compared in order to understand how the individual systems affect overall education policy. The overall findings of each nation are taken and compared to that of the United States and policy suggestions are drawn based on the history and educational structures in the U.S. The policy that is offered is intended to take in account what limitations and variances that the United States has and offer the best solutions, while also taking into account what has been successful in other nations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".