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Record W3216810133 · doi:10.1017/9781108878623.010

Like a Prayer

2021· book-chapter· en· W3216810133 on OpenAlexaff
Paul Downes

Bibliographic record

VenueCambridge University Press eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsPoliticsRhetorical questionDeferenceResistance (ecology)Political scienceLawBlameSociologyLiteratureArtPsychology

Abstract

fetched live from OpenAlex

How might a close reading of the language of revolutionary-era anti-slavery petitions contribute to a broader understanding of the politics of the American founding? This chapter focuses on one of the earliest surviving examples of African American political writing, the petition submitted to the Massachusetts House of Representatives in January 1773, by an author named FELIX. Revolutionary republicans came to disparage the petitionary form, because it had failed to persuade King George to defend his colonial subjects. The petition’s conventional language of deference and its tendency to “pray” or plead rather than to demand or insist led many colonists to reject the form in favor of far more assertive declarations of individual and collective right. By reanimating the petition, however, African Americans like FELIX not only contributed to the work of anti-slavery agitation; they also, as this chapter suggests, registered resistance to some of the dominant political ideas of the republican revolution. Drawing on historical studies of the significance of the petition in the colonies as well as accounts of the petition’s key formal and rhetorical features, this chapter makes the case for a specifically African American contribution to the political discourse of the founding.

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: Other · Consensus signal: Other
Teacher disagreement score0.052
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.006
Scholarly communication0.0070.009
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0520.019

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 head0.029
GPT teacher head0.238
Teacher spread0.208 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooks→Same topicAmerican Constitutional Law and Politics→French-language works237,207→