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Record W4388693248 · doi:10.1093/jsh/shad081

<i>Since Time Immemorial: Native Custom and Law in Colonial Mexico</i> Yanna Yannakakis

2023· article· en· W4388693248 on OpenAlexaffabout
Nora E. Jaffary

Bibliographic record

VenueJournal of Social History · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Studies in Latin America
Canadian institutionsConcordia University
Fundersnot available
KeywordsColonialismHistoryPolitical scienceArt historyArchaeology

Abstract

fetched live from OpenAlex

Indigenous custom in colonial Mexico, we learn from Yanna Yannakakis’s superb new study, was not, as sometimes romantically conceived, rooted in “oral tradition, grounded in popular memory,” and uniformly signifying “the will of the community” (200). Nor is it accurate to conceive of the legal concept and social practice of custom in sixteenth- to eighteenth-century Mexico as suspended in an (immemorial) pre-contact time capsule that operated in isolation from the legal codes of Spanish colonists. Custom, which Yannakakis defines as “a social practice that over time takes on the normative power of law within a territorially based community” (2) was not immobilized at the moment of Spanish contact. Instead, the author shows how indigenous actors constantly reformulated the meanings and applications of custom in New Spain’s courts and in dialogue with European thinking, tradition, and models. Innovating from earlier understandings of custom, Yannakakis’s reading is aligned with Bianca Premo’s recent formulation of indigenous communities’ eighteenth-century judicial articulations of “custom today,” claims of custom that evolved in response to changing conditions and that sometimes defended wider community rights, but also might be mobilized in support of individual or group interests instead.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.113
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.005
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.020
GPT teacher head0.306
Teacher spread0.285 · 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
GenreOther

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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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