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Record W3198191925 · doi:10.1111/ajps.12660

Restoring Anáhuac: Indigenous Genealogies and Hemispheric Republicanism in Postcolonial Mexico

2021· article· en· W3198191925 on OpenAlexaff
Arturo Chang

Bibliographic record

VenueAmerican Journal of Political Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Society in Latin America
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIndigenousEmancipationMemorializationPoliticsEliteSociologyEmpireGender studiesHistoryAestheticsPolitical scienceLawArt

Abstract

fetched live from OpenAlex

Abstract This article turns to postcolonial Mexico to analyze the importance of Indigenous political thought for the transformation of radical republicanism during the Age of Revolutions. I argue that Mexican insurgents deployed Indigenous genealogies to instantiate what I call “restorative revolution,” a form of revolutionary thinking that prioritized memorialization over absolute foundation. Mexico's restorative project began with calls for the return of the Anáhuac Empire, an Indigenous genealogy that memorialized histories of popular self‐rule to legitimize postcolonial demands. I suggest that the Anáhuac movement transformed the principles of radical republican thought by mobilizing around religious, plebeian, and hemispheric identities. Each of these characteristics problematizes dominant interpretations of republicanism as a secular, elite, and national enterprise. This article uses popular objects and archival ephemera to illustrate the importance of engaging with the political contributions of marginalized groups from the spaces, practice, and languages they used to envision postcolonial emancipation in collective terms.

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)0.001
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: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0000.001
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 head0.014
GPT teacher head0.337
Teacher spread0.323 · 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

Citations16
Published2021
Admission routes1
Has abstractyes

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