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Record W4313429749 · doi:10.6018/ayc.524001

Convention or Originality?: The Attributes of Christian Children in Latin Epigraphy

2022· article· es· W4313429749 on OpenAlexaff
Leonard A. Curchin

Bibliographic record

VenueAntigüedad y Cristianismo · 2022
Typearticle
Languagees
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHumanitiesEpigraphyArtPietyHeavenLiteraturePhilosophyTheology

Abstract

fetched live from OpenAlex

The Latin tomb inscriptions of Christian children show surprising variety in the phrases and epithets used to describe the deceased. While some are conventional attributes expressing the innocence or piety of the child, others are more imaginative, original and even unique. The inscriptions record qualities such as smallness of the child; modesty; intelligence; devotion to God. They lament the child's premature death, but forsee its future in heaven. The inscriptions also reflect the grief and love of bereaved parents, suggesting genuine emotions. Las inscripciones funerarias latinas de niños cristianos muestran una variedad sorprendente en las frases y los epítetos utilizados para describir los muertos. Unos son atributos convencionales que expresan la inocencia o la piedad del niño; otros son más imaginativos, más originales, y incluso únicos. Las inscripciones registran cualidades tales como la pequeñez del niño; modestia; inteligencia; devoción a Dios. Se lamenta la muerte prematura del niño, pero se preve su futuro en el cielo. Las inscripciones reflejan también el dolor y el amor de los padres desolados, y con eso sugieren emociones genuinas.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.010
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.036
GPT teacher head0.324
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

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