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Record W2623036757

DEEP DECOLONIZATION: Latin America and Connected Histories of the Postcolonial World

2016· article· en· W2623036757 on OpenAlexaff
Leila Bijos

Bibliographic record

VenueUnoesc International Legal Seminar · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCuban History and Society
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsLatin AmericansIndigenousColonialismRacismDecolonizationPoliticsColonizationPortugueseEthnologyPopulationRace (biology)Prejudice (legal term)HistoryPolitical scienceGeographyGender studiesSociologyLawDemographyEcologyArchaeologyBiology
DOInot available

Abstract

fetched live from OpenAlex

This paper examines deep colonization in Latin America and the connected histories of the postcolonial world. It critically examines race, racism and colonialism in the history of Latin America, and the legal steps taken to minimize the consequences of prejudice and exclusion. It has identified exploitable individuals and populations for subjection, and indicates the scope of deep colonization in the continent attempting to remove the concept of skin color and other physical attributes as superficial indicators of social, political, or economic conditions. Spaniards and Portuguese colonizers in Latin America have invaded, subjugated, and occupied the territory without the consent of the indigenous inhabitants.  In Brazil, the Portuguese colonizers have tried to subjugate the indigenous population and they refused to subdue to their power, then slaves were brought from Africa to coffee and sugar plantations. This essay examines deep colonization in Latin American, and the economic and political contexts. The main question is what is colonization? This involves a clarification of the relationship between the concept of racism and a number of related concepts as race and colonization, as well as connected histories of the postcolonial world in Latin America.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.952
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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 teacher head, 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
Published2016
Admission routes1
Has abstractyes

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