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Record W2735143969

The Viewpoint of Posterity: The Age of Discoveries Seen through the 17th and 18th Centuries

2010· article· en· W2735143969 on OpenAlexaboutno aff
Marica Milanesi

Bibliographic record

VenueMédiévales · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryQuarter (Canadian coin)PoliticsClassicsPhenomenonAncient historyGeographyArchaeologyPhilosophyEpistemologyLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

In the nineteenth century, it was not unusual to consider the idea of the “Great Geographical Discoveries” as a phenomenon confined to the “century of discoveries”, pioneered by Christopher Columbus and Vasco da Gama, which was universally accepted as the starting point of a new turn in the history of the world. The aim of this article is to prove that in the seventeenth and eighteenth century the chronological definition of the “Great Geographical Discoveries” and the importance given to those discoveries were varied and depended on the political strategies of governments. After the last quarter of the sixteenth century, discoveries were no longer considered as responsible for significant progress in knowledge, a sharp contrast to what they had represented in the first half of that century. During the second half of the seventeenth century, they were seen as full of mistakes and erroneous certainties of which geography had to free itself by systematic exploration and the use of observational astronomy: it was that corrective process which was considered by its protagonists as the real era of the Great Geographical Discoveries.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.021
Scholarly communication0.0100.011
Open science0.0010.006
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0090.001

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 head0.017
GPT teacher head0.221
Teacher spread0.203 · 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 designQualitative
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
Published2010
Admission routes1
Has abstractyes

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