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Record W2322842222 · doi:10.1525/sop.2013.56.3.377

The State Giveth and the State Taketh Away? The Antislavery Movement and the Black Franchise in the United States, 1691–1842

2013· article· en· W2322842222 on OpenAlexaff
Art Budros

Bibliographic record

VenueSociological Perspectives · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMilitantSuffrageDemocracyState (computer science)Political scienceVotingPolitical economyPoliticsLawCriminologySociology

Abstract

fetched live from OpenAlex

Although the franchise is the centerpiece of U.S. democracy, serious scholarly study of the black franchise has been limited to the Reconstruction and Civil Rights eras. Consequently, the author examines black suffrage in the United States during 1691–1842 using event history methods and an original data set. Focusing on the neglected relationship between the antislavery movement and black suffrage, the author reports that disruptive and militant activism, warfare, and partisan politics influenced this phenomenon. There also is support for a generational model of movement success. The evidence clarifies two unsettled issues: (1) whether movements matter and (2) the impacts of conventional, disruptive, and militant protest on movement success. Moreover, as institutionalism predicts, voting rules spread across states through mimicry; and as group threat theory predicts, free black presence adversely affected black suffrage. The findings clarify why it took three and a half centuries for the American democracy to accept a race-blind franchise.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.270
Teacher spread0.256 · 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 designQualitative
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

Citations8
Published2013
Admission routes1
Has abstractyes

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