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Record W2338317423 · doi:10.3167/hrrh.2015.410203

The Emotional Disturbances of Old Age: On the Articulation of Old-Age Mental Incapacity in Eighteenth-Century Tuscany

2015· article· en· W2338317423 on OpenAlexvenueno aff
Mariana Labarca

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArticulation (sociology)Sociocultural evolutionContext (archaeology)NarrativePsychologyNegotiationMental healthDevelopmental psychologySociologyPoliticsPsychotherapistLinguisticsPolitical scienceHistorySocial scienceLawAnthropology

Abstract

fetched live from OpenAlex

This article explores the role attributed to disturbed emotions in the understanding of old-age mental incapacity in eighteenth-century Tuscany. It claims that interdiction procedures provided a fertile forum for the negotiation of what constituted mental incapacity in old age, which progressively involved a discussion on accepted or proper emotional reactions. Delving into the language employed in interdiction narratives, it argues that references to disturbed emotional states were increasingly employed as a means of providing evidence of disordered states of mind. It also suggests that the constituent elements of mental incapacity and the emotional reactions deemed indicative of its presence were dependent on the familial and sociocultural context in which the behavior was identified. Interdictions thus reveal the articulation of a collective, culturally embedded language of mental incapacity that was profoundly entrenched in the formulation of behavioral norms and the shaping of standards of emotional reaction.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.022
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.092
GPT teacher head0.273
Teacher spread0.181 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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