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Record W2904443801 · doi:10.31390/cwbr.20.4.07

Jim Crow North: The Struggle for Equal Rights in Antebellum New England

2018· article· en· W2904443801 on OpenAlexaff
Gordon S. Barker

Bibliographic record

VenueCivil War Book Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsBishop's University
Fundersnot available
KeywordsNewspaperCivil rightsLegislationCensusGovernment (linguistics)LawNew englandHistoryGenealogyPolitical sciencePoliticsSociologyDemography

Abstract

fetched live from OpenAlex

In Jim Crow North: The Struggle for Equal Rights in Antebellum New England, Richard Archer explores the African-American quest for liberty and equality from the early 1700s, a period when slave codes in the Northeast mirrored those put in place in the Chesapeake, through to the outbreak of the American Civil War. Using an array of primary sources, including eighteenth- and nineteenth-century newspapers, government legislation, court records, census data, and personal correspondence, he crafts a gripping story of courageous black New Englanders challenging discrimination.

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)0.002
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.309
Teacher spread0.284 · 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
Published2018
Admission routes1
Has abstractyes

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