Bibliographic record
Abstract
In the medieval to early modern eras, legal manuals used visual cues to help teach the church laws of consanguinity and affinity as well as concepts of inheritance. Visual aids such as the trees of consanguinity or affinity helped the viewer such as a notary, law student or member of the clergy to do the ‘computation,’ or reckon how closely kin were related to each other by blood or by marriage and by lines of descent or collateral relations. Printed riddles in these early legal manuals were exercises to test how well the reader could calculate whether a marriage should be deemed incest. The riddles moved from legal textbooks into visual culture in the form of paintings and cheap broadside prints. This article examines a riddle painting ‘devoted’ to William Cecil when he was Elizabeth I’s principal secretary, before he became Lord Burghley and explores the painting’s links to the Dutch and Flemish kinship riddles circulating in the Low Countries in manuscript, print and painting. Cecil had a keen interest in genealogies and pedigrees as well as puzzles and ciphers. As a remarried widower with an eldest son from a first marriage and children from his longer second marriage, Cecil lived in a stepfamily typical of the sixteenth century in England and Europe. The visual kinship riddles in England and the Low Countries had a common root but branched into separate traditions. A shared element was the young woman at the centre of the images. To solve the riddle the viewer needed to determine how all the men in the painting were related to her as if she were the ego, or self, at the centre of a consanguinity tree. This article seeks to compare the elements that connect and diverge in the visual kinship riddle traditions of the sixteenth and seventeenth centuries in the Low Countries and England.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.005 |
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".