Los cuerpos de la memoria: género y violencia polÃtica en la literatura peruana contemporánea
Bibliographic record
Abstract
The aim of this doctoral thesis is to explore the way in which political violence during the time of the Shining Path guerrilla movement has been represented in contemporary Peruvian fiction and to examine the role of the female figure in the articulation of the collective memory. As the thesis will show, the use of female characters as a means of expressing the trauma of Peru as a nation is relatively recent and is limited in particular to the first decade of the twenty-first century. In this sense, the reassessment of the role of women in the conflict is inseparable from the important contribution made by the Truth and Reconciliation Commission, whose final report, published in 2003, contributed decisively to reassessing the participation of women in the organizational structure of the Shining Path and in bringing to light the testimonies of Peruvian women who were victims of violence at the hands of both the Shining Path and the Peruvian Army. In addressing this topic, my research focuses on the analysis of three novels: La hora azul (2005), by Alonso Cueto; Confesiones de Tamara Fiol (2009), by Miguel Gutiérrez; and Radio Ciudad Perdida (2007), by Daniel Alarcón. These novels are among the most widely read and critically acclaimed works in Peruvian literature in dealing with the period, and they also share the fact of having been written by male authors. Although there are also works on this period written by women, what I argue in this thesis is that the reassessment of the female figure and its relationship with violence in Peruvian fiction has been dominated, in practice, by a male perspective which, although it attempts to recover the silenced voice of women, nevertheless continues to interpret it with reference to what are considered to be essentially female stereotypes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".