Bibliographic record
Abstract
Preface The research for this book was made possible through a generous grant from the Economic and Social Science Research Council (ESRC), Grant Number RES-223–25–0074. We are particularly grateful to the ESRC for its support. Special thanks are also due to Stewart Croft as the Director of the New Security Challenges Programme for his continued encouragement and upbeat enthusiasm for the project. The ESRC grant facilitated an intensive two-year period of fieldwork and travel. On our return to Aberystwyth, the Department of International Politics always provided an inspiring and collegial work environment. The Department was our intellectual home for a decade and occupies a special place in our hearts. To our friends, colleagues and students from Aberystwyth: we are forever grateful for your support, your constructive criticism and challenges – and for all the good times along the way! We also owe thanks to other institutions. The Department of Political Studies at the University of Cape Town kindly accepted us as Visiting Fellows during one of our stays in Cape Town and provided a welcoming and conducive base from which to conduct our research. Very special thanks are due to Neil Walker and the Department of Law at the European University Institute (EUI) in Florence for hosting us during the winter and spring of 2007 and for allowing us the privilege of working in the tranquil and productive surroundings of the EUI. The final stages of the project were completed as Visiting Fellows at the School of Politics and International Studies at the University of Queensland in Brisbane. We could hardly have wished for a more convivial setting in which to finalize the manuscript, and we are very grateful to the School for providing such an enjoyable and intellectually stimulating environment. For the past year, the University of Ottawa has been a welcoming and exciting new institution in which to bring the project to completion. We are very grateful to our colleagues for making it so.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.303 | 0.162 |
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".