How to not have to know: Legal technicalities and flagrant criminal offenses in Santiago, Chile
Bibliographic record
Abstract
Abstract Drawing on ethnographic data gathered in lower criminal courts and in one unit of the Public Prosecutor's Office in Santiago, Chile, I explore the way in which criminal offenses considered flagrant are treated by the Chilean criminal justice system. Citing the literature on legal technicalities, I describe how flagrant criminal offenses are constructed through practices that make it possible for the actors involved to avoid directly referring to the alleged facts. From their identification on the streets by police officers to their reassignment to a different unit of the Public Prosecutor's Office or their adjudication at a criminal court, flagrant criminal offenses are defined by a specific way of approaching the alleged facts, which is translated into specific organizational and documentary practices. The role of these practices contrasts with the apparently marginal role that the detention in flagrante delicto plays in the mechanics of criminal law. As a technicality, the flagrant character of a criminal offense conveys certain epistemological assumptions about how to determine what happened and what exactly constitutes the criminal offense. More specifically, it conveys assumptions about what cannot, for the moment, be known and that can, therefore, be ignored throughout the bureaucratic and judicial process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".