Undergraduate Research-Methods Training in Political Science: A Comparative Perspective
Bibliographic record
Abstract
Abstract Unlike other disciplines in the social sciences, there has been relatively little attention paid to the structure of the undergraduate political science curriculum. This article reports the results of a representative survey of 200 political science programs in the United States, examining requirements for quantitative methods, research methods, and research projects. The article then compares the results for the United States with a survey of all political science programs in Australia, Canada, Finland, the Netherlands, Norway, Sweden, and the United Kingdom. The results suggest (1) that the state of undergraduate methods instruction is much weaker in the United States than indicated in previous research, (2) this pattern is repeated in other countries that emphasize broad and flexible liberal arts degrees, and finally (3) this pattern of weak methods requirements is not found in more centralized, European higher education system that emphasize depth over breadth. These countries demonstrate a consistent commitment to undergraduate training in research methods that is followed up with requirements for students to practice hands-on research. The model of weak methods requirements in the discipline is not the norm internationally, but differs depending upon the type of higher education system.
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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 | 0.031 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".