Bibliographic record
Abstract
ac k now l e dg m e n ts during the summer of 2014, Ted Peña introduced me to a set of curious dolia at Regio I Insula 22 at Pompeii, entrusting me to design my own research proj ect as part of the Pompeii Artifact Life History Proj ect; little did I know that those after noons meticulously documenting dolia would lead to years of fascination with these vessels.The proj ect began to expand and take shape in 2015 as a doctoral dissertation, and it has grown and benefited enormously over the years from the generosity and spirit of many individuals and communities.It is a pleasure to acknowledge them here.The Gradu ate Group in Ancient History and Mediterranean Archaeology, as well as the Center for the Tebtunis Papyri and the Department of Classics at the University of California, Berkeley, formed my home base during the early years and encouraged me from day one to expand my horizons and pursue multi-and interdisciplinary approaches.Ted's vast knowledge of Roman pottery and his critical eye and attention to detail helped me better clarify and support my observations.Carlos Noreña provided invaluable guidance and helped frame and shape the project, pushing me to expand on the broader significance of the data.I was most fortunate to have spent 2016-2017 as the recipient of the Andrew W. Mellon Pre-doctoral Rome Prize at the American Acad emy in Rome.They say being at the American Acad emy in Rome changes your life and perspective for a reason.Fellows and friends at the acad emy provided good com pany, cheer, and a warm and intellectually stimulating community.Seeing and exploring the city through their eyes helped me notice new things and pre sent my findings to a broader audience.Three generous scholars I had the good fortune to meet through the American Acad emy in Rome greatly influenced this proj ect: Kim Bowes, Lisa Fentress, and Lynne Lancaster gave generous feedback, and their insights prompted me to confront why this proj ect matters and how to make that come across most effectively.Lindsay Harris organized helpful writing groups to workshop our ideas and drafts.Giulia Barra secured permissions to access diff er ent sites and materials during the early, critical stages of the proj ect.The American Acad emy library, especially the support of Sebastian Hierl, was instrumental in accessing the Cosa Archive.The acad emy remained my home base in my final year as a gradu ate student, supported by the University of California Dissertation Year Fellowship, and has continued to be an invaluable resource for me and my proj ect over the years.Since I joined the faculty in 2018, Prince ton University has provided an intellectually stimulating community.I would like to thank my colleagues in the Department of Classics for their support, encouragement, advice, and enthusiasm for my proj ect over the years, especially
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.371 | 0.250 |
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".