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Mulattoes and<i>métis</i>. Attitudes toward miscegenation in the United States and France since the seventeenth century

2005· article· en· W1979796498 on OpenAlexaboutno aff
George M. Fredrickson

Bibliographic record

VenueInternational Social Science Journal · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsTypologyPariah groupRace (biology)EmpireConsistency (knowledge bases)White (mutation)HistoryIdeal (ethics)Gender studiesAmbivalenceSociologyDemographyEthnologyGenealogyPolitical scienceAnthropologyPsychologySocial psychologyLawAncient historyPolitics

Abstract

fetched live from OpenAlex

This essay surveys and compares American and French attitudes toward miscegenation or métissage since the extensive contacts with non‐European peoples that began in the Atlantic world of the seventeenth century. It develops a typology of possible responses to such race mixture and argues that the English colonies that became the United States quickly developed a highly restrictive attitude toward racial intermarriage, especially between blacks and whites, that has persisted through most of American history and is still influential today. The French in the eighteenth, nineteenth and early‐to‐mid twentieth century often adhered to concepts of race as innate or biologically determined, but their attitudes toward interracial marriage or concubinage tended to be more pragmatic. In some situations French theorists of race and empire defended and even advocated certain forms of métissage . The difference can be summed up as follows: white Americans have historically pursued the ideal of racial purity with much more intensity and consistency than the French. The difference is best explained with reference to the unique status of African‐Americans as a colour‐coded pariah group with no real equivalent in metropolitan France.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.112

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 studies0.0040.003
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.317
Teacher spread0.302 · 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 designQualitative
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

Citations19
Published2005
Admission routes1
Has abstractyes

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