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Record W3112341764 · doi:10.2979/indimagahist.116.4.02

The Underground Railroad in Jefferson County, Indiana: An Interracial Partnership Ahead of Its Time

2020· article· en· W3112341764 on OpenAlexaboutno aff
Raley

Bibliographic record

VenueIndiana Magazine of History · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsWhite (mutation)Underground RailroadGeneral partnershipHistoryLawArchaeologyPolitical science

Abstract

fetched live from OpenAlex

The history of the Underground Railroad has long been marked by contentious debate. Surviving evidence from Jefferson County, Indiana, sheds new light on the day-today operations of the Underground Railroad in southeastern Indiana and the Ohio River border region. Historian J. Michael Raley examines the complex interracial network of fugitive slaves, their enslaved and free black families and friends, the free black residents of the Georgetown community in Madison, Indiana, and white abolitionists from area churches and antislavery societies. Their efforts were not without risk. In aiding runaway slaves in their flight northward, people of color secretly collaborated with trusted whites at grave peril to themselves and their families, and despite all efforts, fugitives from slavery far too often were recaptured in route. For those who succeeded in reaching Canada as well as for those who aided them, however, the potential dangers were always more than worth the risk.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.545

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0130.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.042
GPT teacher head0.290
Teacher spread0.248 · 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
Published2020
Admission routes1
Has abstractyes

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