Bibliographic record
Abstract
The concluding chapter summarizes the case for embracing a wider approach to the deep intellectual roots of the IPE field in the pre-1945 period that goes beyond the common focus on just thinkers from Europe and the United States and the debate between economic liberals, neomercantilists, and Marxists. The wider approach of this volume highlights important contributions made by thinkers from outside Europe and the United States in the pre-1945 era as well as important debates both within each of the three orthodoxies and with perspectives beyond them. In addition to providing a more comprehensive history, this wider approach can help to strengthen efforts to foster more “global conversations” in the field of IPE today, to improve interpretations of contemporary political discourse as well as to contribute to the study of topics that are attracting growing interest within current IPE scholarship.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.016 | 0.024 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.034 | 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; 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".