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Record W3007871687 · doi:10.4000/e-spania.34150

Conquérir, errer, négocier, Legazpi et ses hommes dans les îles Visayas (Philippines), 1565-1570

2020· article· fr· W3007871687 on OpenAlexaff
Clotilde Jacquelard

Bibliographic record

Venuee-Spania · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsInstitut d'Histoire de l'Amérique Française
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Dans la logique proposée par l’intitulé du colloque « Les dynamiques de pouvoir dans les mondes ibériques : construire, exercer, résister (XVIe-XVIIIe siècles) » cet article s’attache à réfléchir sur « construire » la domination, soit interroger la spécificité de la conquête des Philippines, une conquête de deuxième génération, qui se produit dans les premières année du règne de Philippe II et non plus sous celui de Charles Quint ; une conquête qui, selon ce qui se dégage de la documentation officielle, tient compte de l’expérience américaine antérieure comme des polémiques suscitées par les conquêtes continentales.

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 score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.289
Teacher spread0.239 · 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
Published2020
Admission routes1
Has abstractyes

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