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Record W2341028898 · doi:10.3167/hrrh.2015.410202

In the Shadow of the Gallows: Symptoms, Sensations, Feelings

2015· article· en· W2341028898 on OpenAlexvenueno aff
Adriano Prosperi

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsWitnessShameShadow (psychology)SadnessContext (archaeology)BattleKey (lock)FeelingPower (physics)PsychoanalysisPsychologyAestheticsHistorySocial psychologyPhilosophyAngerLawPolitical scienceAncient history

Abstract

fetched live from OpenAlex

Through the fascinating late sixteenth-century legal battle over the inheritance of the Florentine nobleman Giovambattista di Bindaccio Ricasoli Baroni, in which the young Galileo Galilei appeared as a key witness, this article reflects on two key categories of emotion of the era: melancholy and terror (specifically, fear of death). In analyzing these emotions, which hounded the unfortunate Ricasoli throughout his life, the article shows that, far from being the private sentiments of a single pathological individual, these emotions reflected the mood of people living in an era when the shadow of the oppression of arbitrary power in this world and of the possibility of eternal suffering in the next were particularly salient. Moreover, seemingly perennial emotions like sadness or the fear of death or shame, far from being unchanging, can take different and unpredictable configurations in a precise historical context, based on impulses and conflicts related to the power relations and the mental patrimony of that society.

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)0.003
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.304
Teacher spread0.209 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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