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Record W4392336996 · doi:10.1515/9781782047728

Order and Disorder in the British Navy, 1793-1815

2016· book· en· W4392336996 on OpenAlexaboutno aff
Thomas Malcomson

Bibliographic record

VenueBoydell and Brewer eBooks · 2016
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNavyOrder (exchange)HistoryPsychologyPsychoanalysisComputer scienceEconomicsArchaeology

Abstract

fetched live from OpenAlex

How did the British navy maintain authority among its potentially disorderly crews? And what order exactly did it wish to establish? Churchill once famously remarked that he would not join the navy because it was "all rum, sodomy and the lash". How far this was true of the navy during the French Revolutionary and Napoleonic Wars is the subject of this important new book. Summary punishments, courts martial, flogging and hanging were regularly made use of in this period to establish order in the navy. Based on extensive original research, including a detailed study of ships' captain's logs and muster tables, this book explores the concepts of order and disorder aboard ships and examines how order was preserved. It discusses the different sorts of disorder and why they occurred; argues that officers toosometimes pushed against the official order; and demonstrates that order was much more than the simple enforcement of the Articles of War. The book argues that the behaviours that were punished, how and to what degree reveal what the navy saw as most resistive or dangerous to its authority and the order it wanted established. In addition, it considers the role of patronage in shaping order, outlining how this was affected by Admiralty moves to centralise appointments, and shows that acts of disorder were plentiful, and increasing, in this period, and that the imbalance in court martial outcomes for sailors, marines and warrant officers, in comparison to commissioned officers, points to a flawed system of justice. Overall, the book provides an extremely nuanced picture of order and how it was preserved. Thomas Malcomson is a Professor in the School of Liberal Arts and Sciences at George Brown College, Toronto, Ontario. He completed his doctorate in history at York University, Toronto.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.678
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.185
Teacher spread0.166 · 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
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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