Bibliographic record
Abstract
Emblems—pictorial designs with accompanying mottoes and epigrams— helped to shape virtually every form of verbal and visual communication in the West during the sixteenth and seventh centuries. A recent re-awakening of scholarly interest in the emblem has brought to light the difficulty of locating and consulting the unorganized mass of available material. Recognizing the need for a large-scale systematic index to the emblem, the editor organized a symposium at McGill University to discuss the possibilities of preparing such an index. The resulting papers by six symposium participants— Barbara Becker-Cantarino, Peter M. Daly, Peter Erb, G. Richard Dimler, Lorelei Robins, and Alan Young—contribute to our knowledge of the emblems of Peacham and Corrozet, the Dutch love emblems, the Jesuit emblem, and emblems used in books of mediation. The essays also discuss the problems and procedures involved in preparing an Index Emblematicus , a work which would serve scholars working in the fields of literature, art, culture, religion, history, and the languages. The volume is richly illustrated with over forty emblem reproductions.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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".