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Record W1971147317 · doi:10.1163/157006508x369893

To Pray, To Work, To Hear, To Speak: Women in Roman Streets c. 1600

2008· article· en· W1971147317 on OpenAlexaff
Elizabeth S. Cohen

Bibliographic record

VenueJournal of Early Modern History · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsYork University
Fundersnot available
KeywordsSeclusionLivelihoodPleasureGovernment (linguistics)Private spaceSpace (punctuation)HistoryGender studiesWork (physics)SociologyLawPolitical sciencePsychologyArchaeologyEngineering

Abstract

fetched live from OpenAlex

Abstract Using pictures, city regulations, and judicial records, this essay claims a place for women of varying rank and status in the street life of early modern Rome. It revises the conventional binary of male public realms and female domesticity that, reinforced by scholarly expectations of Mediterranean gendered seclusion, obscures a necessary female presence in the city. In urban spaces outside their homes beggars, prostitutes, servants, working wives, nubile daughters, and even gentlewomen faced risks, but also cadged opportunities. Though excluded from government and corporate decision-making, women routinely ventured into the streets in pursuit of many goals: heavenly salvation, earthly livelihood, neighborly support, vital information, or momentary pleasure. While Rome's patterns of physical and demographic growth distinguished it in important respects from other Italian cities, it is nevertheless likely that, as in Venice, these female uses of urban space had analogues elsewhere.

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 score0.013
Threshold uncertainty score0.034

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 studies0.0100.006
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.059
GPT teacher head0.215
Teacher spread0.157 · 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

Citations42
Published2008
Admission routes1
Has abstractyes

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