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Record W7124818795

Rediscovered Visual Documents of the Portuguese Estado da India: The Filippe Nery Xavier Collection

2024· book· en· W7124818795 on OpenAlexaboutno aff
Sidh Daniel Losa Mendiratta, Giuseppe Resta, Antonieta Reis Leite

Bibliographic record

VenueIris (Roma Tre University) · 2024
Typebook
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsnot available
Fundersnot available
KeywordsPortugueseColonialismQuarter (Canadian coin)Government (linguistics)State (computer science)Relation (database)
DOInot available

Abstract

fetched live from OpenAlex

The so-called Filippe Nery Xavier Collection in the British Library includes an unresearched set of manuscript visual documents relating to the Portuguese State of India (Estado da Índia), dating between the mid-seventeenth century and the second half of the nineteenth century. The collection was in Goa in the early years of the twentieth century and was acquired in 1978 by the British Library from a Parisian rare book dealer. The collection also includes printed maps and statistical charts. Filippe Nery Xavier [1801-1875] was a Goan civil servant working for the Portuguese colonial government and a self-taught historian who wrote extensively on Goa. Among his many interests was the process of lithographic printing, which developed in Goa during the second quarter of the nineteenth century. As a source of rediscovered visual documents related to the port cities and territories of the Estado da Índia, the Filippe Nery Xavier Collection was studied in the framework of the PORTofCALL project (FCT/PTDC/ART-DAQ/4357/2021). This research project aims at studying the relation between the early modern African-Asian-European encounters and the cultural landscapes of the Indian Ocean’s port settlements frequented by the Portuguese.

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: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0050.003
Scholarly communication0.0060.001
Open science0.0010.002
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 head0.013
GPT teacher head0.252
Teacher spread0.240 · 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
Published2024
Admission routes1
Has abstractyes

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