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Record W3202908942 · doi:10.33423/jabe.v22i3.2858

The Purchase of Wax from Flanders by the Merchants of Burgos According to the Notarial Protocols of Alonso González de Nestares y Aguayo (1561-1568)

2020· article· en· W3202908942 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Applied Business and Economics · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical and socio-economic studies of Spain and related regions
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationIntermediaryBusinessCommerceConstraint (computer-aided design)HistoryEconomyAdvertisingEconomic historyMarketingEconomicsEngineeringComputer science

Abstract

fetched live from OpenAlex

Notarial protocols keep thousands of deeds of sale of wax from Flanders. This work focuses on the records of the notary of the city of Burgos (Spain), Alonso González de Nestares and Aguayo. The preserved documentation is quite scarce. Only five files remain with chronological gaps: 1561 (February-June), 1564 (January-August), 1568 (December 1567-July 1568), 1575 (without chronological order), and 1576 (December 1575-December 1576). Despite this constraint, the richness of the data the documents contain will help us better understand the wax trade, a very important product in the daily life of man throughout its history. In the mid-16th century, Flanders became the most important wax supplier in Burgos. Some of the main international merchants are going to be the ones that import the wax and introduce it into the sales channels of the city, closing wholesale deals with other local commercials interested in this business. But the most abundant sales are those made by these local intermediaries to other Burgos, churches, clergy and neighbors of the province; It also allows us to know the price fluctuation.

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)0.002
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.006

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 head0.035
GPT teacher head0.212
Teacher spread0.177 · 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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