Are Quantitative Research Methods to Blame for a Growing Irrelevance of Political Science? A Rejoinder to John Trent
Bibliographic record
Abstract
‘Is political science out of step with the world?’ This question, raised by John E. Trent in a recent issue, is part of a recurring debate about the development of our discipline. In that article, and in a subsequent book with his colleague Michael Stein, John Trent blames adherents of the ‘scientific method’ for political science’s growing irrelevance. We challenge this claim by arguing that Trent falls back on outdated polarities between ‘objective and normative’, and ‘explanation and interpretation’, in order to justify his allegation. We argue for the need to review our methods continuously, rather than dig up a fruitless and biased division between qualitative and quantitative approaches.
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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 | 0.459 | 0.623 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.008 | 0.120 |
| Scholarly communication | 0.024 | 0.040 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.017 | 0.052 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".