The Indian, The Mestizo, and The Impostor: The Fictionality of Race in Inca Garcilaso de la Vega
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".