Ojeda, Almerindo E., project dir. PESSCA: Project on the Engraved Sources of Spanish Colonial Art. Database
Bibliographic record
Abstract
The transition between print and material cultures is one of the vocations of emblems: since Alciato's inaugural work, images and texts from emblem books have been used as a source of inspiration for paintings, sculptures, festival decorations, frescoes, medals, and other media.PESSCA is an extraordinary collaborative database that collects over 6,000 correspondences of artworks and their printed sources-frequently emblematic-with an emphasis on early modern Spanish America.The project was launched in 2005 by Almerindo Ojeda at the University of California, Davis, and was first hosted on Princeton's Almagest platform (now apparently discontinued).Currently, PESSCA is hosted by Fulvio Casali from Soliton Consulting, a private company, with a mirror at the Pontificia Universidad Católica del Perú (artecolonial.pucp.edu.pe). 1 The website navigation is straightforward: beginning from the PESSCA homepage (Fig. 1), users can either use the search bar in the upper-right corner (which searches the entire website), or they can browse the "Archives, " located on the navigation bar.The "Archives" are divided into two main categories, "Subjects" and "Locations, " which are designed as drop-down menus."Subjects" has 16 subcategories, which can also be expanded, and, as one might expect, at least 12 of them are dedicated to Christianity.The subcategories are not based on a controlled or hierarchical vocabulary: for instance, there is a subcategory for "Old Testament" (with 540 occurrences), while the subject of the New Testament is dispersed into other categories such as "Jesus Christ" (1,179 occurrences), "Virgin Mary" (642 occurrences), and so on.Also, not all of these subcategories are subject-based (e.g., "Architecture, " "Design, " "Ornamentation, " and "Inscriptions").1.More information about the history of the project can be obtained on the "Us" page, accessed from the site's main navigation bar.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.171 | 0.180 |
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".