Reconstructing Historical Geographies of the Dirty War in Mexico: The Challenges of Working with the Archives of the Dirección Federal de Seguridad
Bibliographic record
Abstract
As part of the process of democratic transition, the Mexican government opened the archives of the Dirección Federal de Seguridad in 2002. Created after World War II, the mandate of this agency was to protect the country from internal and external subversion. When decommissioned, the archives joined the Archivo General de la Nación, which is housed in the former Lecumberri prison in Mexico City. The archives help to outline the development of new technologies of state power that underpinned Mexico’s Dirty War. Working with such documents therefore poses significant methodological and ethical challenges. This article addresses several of these challenges. It first addresses the complex transitions represented through the prison-turned-archive and highlights the ways in which access to the archives has been politicized and tenuous. The article draws on the concepts of “state fixations” and “fugitive landscapes” developed by Craib (2004 Craib, R. B. 2004. Cartographic Mexico: A history of state fixations and fugitive landscapes. Durham, NC: Duke University Press.[Crossref] , [Google Scholar]) to explore the spatialities of power and resistance represented through the archives. Drawing on archival material that documents a significant university movement that emerged in the 1970s in Oaxaca, this article presents a range of strategies for building an explicit geography of student mobilization and state repression in Mexico.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| 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".