Rewrapping Indianness for Spain: The Peritextual Representation of Native North American Identity in Literary Translations1
Bibliographic record
Abstract
When literature gets translated and published in the target market, the peritextual elements of the books get modified and updated because of commercial and aesthetic issues. If the translation involves identities very different from that of the target culture, then the peritexts offer a great amount of information about the ethnic representations that are accepted, welcome and customary as for the identities of the source culture and its members. This paper analyzes such a situation in relation to the Spanish translations of Native American written literature. By means of examining the peritexts of the available renditions in Spain, it is possible to establish if the publishing houses share a common image of Indianness, how it and its alternatives are used linguistically and visually, and what are the consequences of those cultural representations. This paper also includes a revision of the convergence of Translation Studies, Native American Studies and Imagology Studies in researching these renditions, and it stresses the importance of using this multidisciplinary point of view on the research materials.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".