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Record W2975590150 · doi:10.3138/ecf.32.1.123

Transformations of Gender and Race in Maria Riddell’s Transatlantic Biopolitics

2019· article· en· W2975590150 on OpenAlexvenueno aff
Melissa Bailes

Bibliographic record

VenueEighteenth-Century Fiction · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsnot available
Fundersnot available
KeywordsForegroundingRace (biology)Natural (archaeology)PoliticsConversationGender studiesEthnologyHistoryWhite (mutation)SociologyAnthropologyArchaeologyArtLiteraturePolitical scienceBiologyLaw

Abstract

fetched live from OpenAlex

Maria Riddell’s Voyages to the Madeira, and Leeward Caribbean Isles (1792), offers new understandings of the mutability and hybridity of race, gender, sex, and nation in the eighteenth-century British Atlantic colonies. By foregrounding Riddell’s engagements with natural history, this article places botanical and zoological classificatory systems in conversation with her depictions of how white women colonists and enslaved African labourers utilized the natural world. In addition to the ideas of contemporary naturalists, such as Linnaeus, Leclerc, comte de Buffon, and Smellie, Riddell’s work is also situated in relation to that of Erasmus Darwin, Edward Long, and Janet Schaw. At a time of significant political revolutions, Riddell’s travel narra tive affords insight into implications for the Caribbean colonies and their function as an environment of sociobiological transformation. While eighteenth-century writing often represented the West Indies as a site of biological and social degeneration, this essay shows that they were also depicted as a site of improvement and a sphere of knowledge-making that produced hybrid identities, knowledges, and cultures.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.098
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0100.016
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.002
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 head0.261
Teacher spread0.247 · 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 designTheoretical or conceptual
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

Citations2
Published2019
Admission routes1
Has abstractyes

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