Bibliographic record
Abstract
Kanaan.Georgetown professors who served as panel discussants later remarked that the quality of some presentations surpassed the sophistication of recent graduate-level dissertations.Judging by their comments, the conference brought together some of the best young minds in economics as they approached the frontiers of research in the discipline.I never imagined in March 2001 that the first Carroll Round would attain the heights realized one year later, or for that matter even exist.Over the past five years, the event has grown in size and scope beyond my initial hopes.The participation of Nobel Laureate John F. Nash, Jr. in 2004 marked a special peak in the evolution of the conference, and I hope that over time students from the developing world will be able to attend.I continue to enjoy meeting participants and learning about their research interests.As they share in the excitement of presenting their work and the occasional trepidation of fielding questions, I feel humbled to be among such gifted individuals.In fact, alumni from previous years have advanced to graduate study at Berkeley, Chicago, MIT, Michigan, Oxford, Princeton, Yale, and Wisconsin, as well as top government and finance positions around the country.This group of former conference participants has truly grown into a professional and academic network unlike any other for young economists.In closing, I would like to thank the Kazanjian Foundation for their generous support, which made the publication of these Carroll Round Proceedings possible.I also would like to extend my unwavering gratitude to the members of the inaugural Carroll Round Steering Committee without whom this history would have remained fiction.I have great respect and admiration for successive Chairs Seth Kundrot, Meredith Gilbert, and Erica Yu as they assumed leadership of the conference.And, I am particularly grateful to current Chair Marina Lafferriere for joining the Committee as a freshman, carrying on the Pembroke tradition, and returning to lead the Carroll Round as a senior.Other past and present Committee members have tirelessly ensured the success of the conference each year and deserve our appreciation.Finally, I must thank Mitch Kaneda who has miraculously preserved my vision for the Carroll Round over the years and watched over past Committees as they built upon its initial success and join the ranks of distinguished alumni.With his continued collaboration and the eagerness of future Georgetown students, I expect that the next chapter in the history of the Carroll Round will far surpass the first five years.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.677 | 0.501 |
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".