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Record W2201609113 · doi:10.33137/rr.v31i2.9184

Black Africans' Religious and Cultural Assimilation to, or Appropriation of, Catholicism in Italy, 1470-1520

2008· article· fr· W2201609113 on OpenAlexvenueno aff
Kate Lowe

Bibliographic record

VenueRenaissance and Reformation · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtAppropriationCONTESTEthnologyHistoryPhilosophyTheology

Abstract

fetched live from OpenAlex

Dans cet article, j’examine trois exemples d’africains sub-sahariens présents dans l’Italie de la Renaissance et qui ont assimilé avec succès les fondamentaux du catholicisme. On considère qu’il était impossible pour les noirs africains en Europe de se réinventer une nouvelle identité sans être préparés à apprendre comment mener une vie de catholique pieux. Toutefois, ce niveau d’assimilation était contesté régulièrement par les Européens ‘blancs’. On en examine trois exemples: le premier concerne les préjugés courants qui empêchaient qu’un couple d’esclaves noirs donne leur enfant le nom d’un saint catholique. Un deuxième exemple consiste en l’introduction d’un donateur noir dans un retable du XVe siècle. Le troisième exemple analyse le contenu religieux du testament d’une femme d’Afrique noire.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

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 studies0.0020.003
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.033
GPT teacher head0.290
Teacher spread0.257 · 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

Citations13
Published2008
Admission routes1
Has abstractyes

Explore more

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