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Record W4210992852 · doi:10.1093/jahist/jaab249

1774: The Long Year of Revolution

2021· article· en· W4210992852 on OpenAlexaboutno aff
Edward G. Gray

Bibliographic record

VenueJournal of American History · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsPunitive damagesNothingContext (archaeology)NarrativeHistoryPoliticsColonialismCONQUESTEconomic historyLawPolitical scienceAncient historyArchaeologyArtLiterature

Abstract

fetched live from OpenAlex

In a sweeping narrative covering “the sixteen months between December 1773 and mid-April 1775,” Mary Beth Norton's newest book recounts “the unprecedented events that occurred in the English colonies of North America during those months” (p. xvi). The most familiar of these events were the colonial responses to the 1773 Tea Act; the subsequent response to three punitive Coercive Acts in 1774; and the creation and convening of the Continental Congress. Norton's emphasis is unapologetically North American. There is practically nothing in her narrative about British politics and the intricacies of parliamentary law making. Nor is there discussion of any larger imperial context—for example, the desperate need to stabilize Britain's prime instrument of South Asian conquest, the East India Company, or the similarly urgent quest to secure Britain's American possessions in the West Indies, the Ohio Country, and what would become Canada. Instead, she offers readers what is surely the...

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: Empirical · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.277
Teacher spread0.258 · 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
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
Published2021
Admission routes1
Has abstractyes

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