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The Afterlife of Uncle Tom

2019· article· en· W2959785441 on OpenAlexaff
Faye Halpern

Bibliographic record

VenueResources for American Literary Study · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMartyrEpithetIncarnationArt historyArtHumanityPerformance artAfterlifeHistoryLiteraturePhilosophyTheology

Abstract

fetched live from OpenAlex

ABSTRACT Uncle Tom's fall from grace took almost a century. Uncle Tom's Cabin (1852) was immediately adapted into stage productions, which foregrounded Tom's humanity. But the high regard in which most people held Tom began to change in the late nineteenth century, when members of the Black audience began to see him as representative of an “Old Negro” type. The twentieth century multiplied the venues in which Tom appeared, but it also witnessed the further erosion of Tom into his present incarnation as an intraracial epithet. This is the story told by Adena Spingarn in her richly researched book, Uncle Tom: From Martyr to Traitor. Although Spingarn's book smooths out some of the interpretive lumps of Uncle Tom and Uncle Tom's Cabin, its simplifications are compensated for by the artifacts it unearths and the attention it pays to the reception of Uncle Tom by a changing Black audience.

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)0.003
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 score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0230.011
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.002

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 head0.007
GPT teacher head0.284
Teacher spread0.277 · 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
Published2019
Admission routes1
Has abstractyes

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