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Record W2294247296 · doi:10.33137/pbsc.v53i1.21417

The Fragmented Armada: The Transmission of an Armada News Pamphlet (pp 107-130)

2016· article· en· W2294247296 on OpenAlexvenueno aff
Meaghan J. Brown

Bibliographic record

VenuePapers of The Bibliographical Society of Canada · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Influence and Diplomacy
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsHistoryClassicsMedia studiesPolitical scienceLawSociology

Abstract

fetched live from OpenAlex

William Cecil’s Copie of a Letter (STC 15412 – 15414.6), consisting of a Letter, its postscript, its printer’s epistle and an additional pamphlet, Certaine Advertisements Ovt of Ireland, was produced in stages in the fall of 1588, an accumulative production attested to by both bibliographical evidence and governmental correspondence. The texts describe England’s military preparations, political climate, and the events of the summer in the form of an epistolary news letter addressed to Don Bernardino de Mendoza, the Spanish Ambassador to France. This attempt to spread the news of Spanish defeat, to delegitimize Catholic news sources, and to dissuade Catholic support for another convoy grew and developed as the political situation unfolded over the summer and early autumn of 1588. This paper examines the production and transmission of Cecil’s propaganda pamphlet to explore the interpretive frameworks that textual producers, both authors and publishers, used to package early modern news.

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)0.015
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 score0.255
Threshold uncertainty score0.507

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0160.011
Scholarly communication0.0120.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.010
GPT teacher head0.254
Teacher spread0.243 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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