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Record W6993067698

No Honour in Death: Analyzing the Debaucherous Death of Empress Valeria Messalina

2024· dissertation· en· W6993067698 on OpenAlexaff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2024
Typedissertation
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHonourEmperorNarrativeCertaintyExtant taxonPower (physics)Reading (process)
DOInot available

Abstract

fetched live from OpenAlex

It is not a certainty that the life of the Julio-Claudian empress Valeria Messalina was any different from the lives of the empresses who preceded her. The written historical record is largely silent on her life before she married the emperor Claudius in 38 CE. During her time in the role of empress, the visual record is reasonably conventional, depicting her as modest, in draping garments, often with one or both of her children at her side. Little was written about her during her tenure as empress. What is securely known is that an official damnatio memoriae, the act of erasing a figure from history, followed her death. Statues of her were likely destroyed or stored. Inscriptions had her name damaged or gouged out. Coins with images of her ceased to be minted and may well have been destroyed. Messalina did not, however, disappear from the historical record, either visual or written. Some seventy years after her death Tacitus, Suetonius, and Cassius Dio wrote her – and her misdeeds – into the historical record. Her death scene is treated with such force that it is difficult to raise the possibility that Messalina was a conventional empress. A powerful death narrative, either positive or negative, colours the life of the deceased; to this day the name Messalina has not recovered from the condemnatory narratives surrounding her death. A comparison of the extant material evidence and written evidence will show the power of a negative death narrative and highlight how the memory of the empress Messalina suffered the consequences.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.519
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.272
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2024
Admission routes1
Has abstractyes

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