Mosaics of Knowledge: Representing Information in the Roman World by Andrew M. Riggsby
Bibliographic record
Abstract
With Mosaics of Knowledge, Andrew Riggsby has produced a very ambitious and thoughtprovoking book. Like Daryn Lehoux’s What Did the Romans Know? [2012], Riggsby’s new book reminds us that the Romans did not see science or technology as we do. However, where Lehoux focuses on a philosophical exploration of how the Romans made sense of the natural world, and why they saw such a different world from the one that we do, Riggsby explores how the Romans understood and used several types of information technology. Here I summarize and comment on what I consider to be the key contributions of each chapter. At the end of the review, I will give some general comments on the book as a whole. Reviewed by: Jason C. Morris, Published Online (2021-08-31)Copyright © 2021 by Jason C. Morris This open access publication is distributed under a Creative Commons Attribution-NonCommercial-NoDerivatives License (CC BY-NC-ND) Article PDF Link: https://jps.library.utoronto.ca/index.php/aestimatio/article/view/37732/28733 Corresponding Author: Jason C. Morris,Independent ScholarE-Mail: Claudius.caecus@gmail.com
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".