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Record W4412122477 · doi:10.33137/rr.v48i1-2.45698

Blindness, Judicial Blinding, and Social Death in Early Modern Germany

2025· article· en· W4412122477 on OpenAlexvenueno aff
Jacob M. Baum

Bibliographic record

VenueRenaissance and Reformation · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicReformation and Early Modern Christianity
Canadian institutionsnot available
Fundersnot available
KeywordsBlindingBlindnessCriminologyPolitical scienceHistoryLawPsychologyMedicineOptometryMEDLINE

Abstract

fetched live from OpenAlex

This article examines the great age of corporal punishments in German-speaking lands to draw attention to the historical intersections between senses, disability, and social death. Between approximately 1400 and 1550, civic and territorial magistrates administered a wide variety of corporal punishments on subjects, including mutilating punishments such as blinding. This article sketches the history of judicial blinding through a close reading of the archival record from the free imperial city of Frankfurt am Main and contextualizes this evidence by reference to the practice in other sites across German-speaking lands. It explains the origins of judicial blinding, analyzes major patterns in how the punishment was administered, and interprets the age of judicial blinding as a long experiment in social death. To make this final interpretive argument, this article shows how those who suffered the punishment embodied the three major criteria associated with social death in modern theoretical discussions of the concept: loss of bodily integrity, loss of social identity, and loss of social networks. Throughout, analysis and interpretation bring together insights from early modern sensory history and disability history.

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)0.002
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 score0.027
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.022
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.001
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 head0.029
GPT teacher head0.256
Teacher spread0.227 · 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
Published2025
Admission routes1
Has abstractyes

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