Domesticating Danger: Coping Codes and Symbolic Security amid Violent Organized Crime in Mexico
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sociologists have long debated how labels are deployed to construct and exaggerate social threats but have yet to consider their use to cope with danger. I draw on qualitative fieldwork conducted in the midst of a gruesome turf war in Monterrey, Mexico, to conceptualize coping codes. These defensive labels emerge in everyday conversation and allow its users to allude to threatening actors without being explicit—in this case, violent organized crime labeled malitos, or little evil guys. They emerge from below and in relation to top-bottom labeling processes they can both challenge and reproduce. Coping codes provide symbolic security by minimizing danger, although at a cost when also used to draw symbolic boundaries between the living and the dead “accused of being into something.” The case calls for further research on coping codes in dangerous contexts, particularly at the onset of unsettled times when people tend to minimize rupture.
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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 | 0.003 | 0.004 |
| 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 | 0.001 |
| 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 it