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Record W2598317038 · doi:10.3138/cras.2016.014

The Economization of Freedom: Abolitionists versus Merchants in the Culture War that Destroyed Pennsylvania Hall

2017· article· en· W2598317038 on OpenAlexvenueno aff
Beverly C. Tomek

Bibliographic record

VenueCanadian Review of American Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyCapital (architecture)BattleCultural capitalValue (mathematics)White (mutation)Privilege (computing)Working classSociologyLawPolitical scienceGender studiesHistoryPoliticsAncient history

Abstract

fetched live from OpenAlex

Throughout US history, white skin has held a non-pecuniary value, described by some as a “wage of whiteness” and, more recently, discussed as “white privilege.” This idea, when placed alongside the sociological concept of “cultural capital,” helps shed light on the importance of working-class whites to the material and ideological battle over slavery and its abolition. The 1838 anti-abolition attack that led to the destruction of Pennsylvania Hall in Philadelphia shows the importance of cultural capital by illustrating how southern planters and northern merchants on the one hand and abolitionists on the other worked to gain the support of working-class whites by stressing the value of the cultural capital that they possessed, no matter how poor they were materially. While the former focused on economic interests in hopes of gaining the support of working-class whites, the latter stressed the importance of cultural ideals such as free speech and freedom of the press. Anti-abolitionists placed a low value on freedom, deeming it less important than trade, but abolitionists ultimately commoditized freedom and highlighted its cultural value.

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.016
Scholarly communication0.0050.006
Open science0.0010.002
Research integrity0.0020.003
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 head0.059
GPT teacher head0.360
Teacher spread0.301 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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