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Record W4280518176 · doi:10.3390/genealogy6020043

Kinship Riddles

2022· article· en· W4280518176 on OpenAlexaff
Lyndan Warner

Bibliographic record

VenueGenealogy · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMarriage and Sexual Relationships
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsKinshipPaintingFamily treeGenealogyInheritance (genetic algorithm)FlemishStigmataSociologyHistoryLawArtArt historyAnthropologyPolitical science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.081
GPT teacher head0.343
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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