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Record W2109590381

"Because I am in All Cultures at the Same Time": Intersections of Gloria Anzaldua's Concept of Mestizaje in the Writings of Latin American Jewish Women Writers

2006· article· en· W2109590381 on OpenAlexvenueno aff
Benay Blend

Bibliographic record

VenuePostcolonial text · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American and Latino Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGender studiesSociologyPatriarchyLatin AmericansQueerNarrativeJudaismFeminismHeteronormativityGeopoliticsIdentity (music)LesbianAestheticsLiteratureHistoryPoliticsArtPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

As a woman who consistently confronts institutionalized racism, class exploitation, sexism and homophobia, Gloria Anzaldua insists on illuminating multiple systems of exploitation that apply to oppressed groups resisting incorporation by dominant cultures. In Borderlands/La Frontera, Anzaldua's theory of the New Mestiza provides a paradigm for looking at how Latin American Jewish women writers also define their narrative form through the concept of mestizaje, or mestizo culture. Moreover, just as Anzaldua's multiple identity as a working-class-origin lesbian of color allows her to include other internal struggles in the analysis, so Jewish women in Latin Ameican, through questioning and deconstructing the patriarchy during recent military tyrannies in that country, have made important contributions in feminist and queer writing. By demonstrating that they are hybrids, Latin American Jewish writers create a space between different worlds. By thus acknowledging the specific struggles across geopolitical lines, feminism can build new bridges and continue to develop as a politically significant body of ideas.

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)0.005
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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.018
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0020.002
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 head0.016
GPT teacher head0.302
Teacher spread0.286 · 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
Published2006
Admission routes1
Has abstractyes

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