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Record W4385698481 · doi:10.1093/ehr/cead104

Disorder, Riot and Governance in Early Tudor London: Evil May Day, 1517

2023· article· en· W4385698481 on OpenAlexaff
Shannon McSheffrey

Bibliographic record

VenueThe English Historical Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsEliteGrievanceHistoryEconomic JusticeImmigrationCriminologyLawPolitical scienceSociologyPolitics

Abstract

fetched live from OpenAlex

Abstract On the eve of the May Day festival in 1517, a night of anti-immigrant violence broke out in London. Though pre-modern English historians have frequently invoked Evil May Day, as it came to be called, it has only recently been given concerted scholarly attention. The riot itself was ordinary, one amongst dozens in the first decades of the sixteenth century; it reveals, as a reflection of endemic grievance, a constellation of tensions surrounding labour, immigration, masculine identities, and governance in early Tudor London. More extraordinary, and heretofore not much noticed, was the Crown reaction to the Evil May Day disturbances, on which this article focuses. The insurrectionists were prosecuted for high treason rather than the minor charge of riot; a multi-day pageant of severe justice punctuated by theatrical reprieves followed. At least fifteen were put to death within London’s city walls and there are indications that the final execution toll was much greater, perhaps as high as forty-three. Such a toll following a mild riot could only have been unexpected and shocking, even if in fact ‘only’ fifteen rather than forty or more were executed. This was a message from the Crown both strategically conceived and emotionally driven by the king’s own rage, fury and fear. Though it was the youthful rioters who constituted most of those put to death in the aftermath, the message was meant primarily for the London civic elite, who had dared to question Crown policy and had failed to control the violence in their city.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Review · Consensus signal: Review
Teacher disagreement score0.499
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.034
GPT teacher head0.228
Teacher spread0.195 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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