Opening the Illustrated Incunable Short Title Catalog on CD-ROM: an end-user’s approach to an essential database
Bibliographic record
Abstract
The Illustrated Incunable Short Title Catalog on CD-ROM (IISTC), now in its second edition, provides an unrivaled wealth of information on fifteenth-century printing and, as a computer database, allows for rapid searching that would not be possible with printed reference works. However, the database’s search interface suffers from numerous problems, as Paul Needham described in a thorough review essay. This article presents a solution to those problems that can be implemented by the end user, and also shows what kind of useful information can be obtained from the IISTC by doing so. The solution entails exporting all records to a very large text file, analyzing the file with scripts written in Perl, importing the information into a full-featured database application, and conducting queries with the database application’s more robust and better documented interface. With the IISTC data directly accessible, the database fields can be manipulated to implement features missing in the original IISTC, including separate fields for each part of the imprint data and a count of recorded copies. Query-generated output demonstrated here include a table of incunables with the highest number of copies recorded in the IISTC; printers of Ulm, the number of their signed editions, and their dates; and the number of signed editions printed each year through the end of the fifteenth century. Sample scripts for recreating the results described here, as well as instructions for implementing them and a discussion of points to consider when doing so, are found in the appendices.
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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.047 | 0.040 |
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".