A machine of the same: Repetition in the foundational discourse of the Argentinean “being” (1976–1983)
Bibliographic record
Abstract
Using the example of the military regime in Argentina (1976-1983) and relevant archival materials, this article demonstrates the prerequisite of exalted language in constructing an enemy and how a discursive 'machine of the same' was put into operation. The author argues that what made this operation unique is its structure of repetition that stimulated "the tendency to merge" what is "foreigner-to-the-ego", and the "enemy outside" into a single concept in the Argentinian national psyche.As a theoretical lens, the author examines the military regime's language through Freud's understanding of groups and civilization and Laplanche's proposition that cultural narratives in the form of mytho-symbolic explanations help us translate the sexual drive and offer a "solution" to the helplessness of the infant-adult.The author further claims that at other times a cultural narration functions as an anti-translation device when set against the emergence of a new net of significations. The nation's founding narrative of an Occidental-Spanish-Catholic "being" that first effaced its indigenous origins and then its Arabic and Jewish inheritance was brought back by the military regime as a mytho-symbolic narration that formed a shield against the repressed remnants of the enigmatic message pressing for a new translation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".