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Record W4200420494 · doi:10.29173/connections43

The Indian, The Mestizo, and The Impostor: The Fictionality of Race in Inca Garcilaso de la Vega

2021· article· en· W4200420494 on OpenAlexvenueno aff
Manuel Garzon

Bibliographic record

VenueConnections A Journal of Language Media and Culture · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLatin American history and culture
Canadian institutionsnot available
FundersInstitut National Du CancerVedecká Grantová Agentúra MŠVVaŠ SR a SAV
KeywordsDepictionPersonaIndigenousLiteratureDescendantMeaning (existential)Reading (process)ColonialismHistoryRace (biology)ArtAnthropologySociologyHumanitiesPhilosophyGender studiesLinguistics

Abstract

fetched live from OpenAlex

Inca Garcilaso de la Vega is perhaps one of the most racially conscious authors of early modernity. In fact, he is the first American-born author to self-identify as a direct descendant of a colonized indigenous nation. As such, Inca Garcilaso understood well the epistemic implications of his biracial and bicultural status (his mestizo condition). Most literary critics have analyzed the incessant reiteration of his mestizaje throughout his texts as a way of countering the racist colonial labels imposed on Amerindians and their descendants. However, there is a complex and somewhat contradictory usage of racial terminology throughout his works. Sometimes Garcilaso claims to be a mestizo, sometimes an Indian, and at times he seems to only highlight his Spanish heritage, depending on the situation. In this sense, Inca Garcilaso’s depiction of his authorial persona is not a straightforward decolonial counter-discourse. Instead, I argue that the Inca Garcilaso that appears in his texts is a fictional author whose deliberately inconsistent use of the different racial labels amounts to a modern decolonial strategy: a critique that ironizes the traditional meaning of racial labels, thus destabilizing their epistemic status. In this paper, I aim to flesh out Garcilaso’s complex decolonial strategy, through a literary reading of his authorial persona.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueConnections A Journal of Language Media and CultureSame topicLatin American history and cultureFrench-language works237,207