‘Trash-talk’ and the production of quotidian geopolitical boundaries in the USA–Mexico borderlands
Bibliographic record
Abstract
This paper draws attention to the intimate frontiers of geopolitics to analyze how quotidian political boundaries are delineated and disputed through mundane discursive practices. My empirical focus is the USA–Mexico borderlands wherein US citizens frequently encounter material evidence of undocumented immigrants and their (unauthorized) border crossings. The materials encountered include identity documents and personal mementos as well as objects needed for survival like water bottles, backpacks, medication, shoes, and clothes. Close encounters with these intimate objects, I argue, have become primary sites wherein everyday framings of belonging are constituted in the borderlands. Drawing on field research in Arizona, I illustrate how cultural prescriptions for bodily comportment in relation to these objects are enlisted in the production and disruption of quotidian framings of ‘American’ or ‘those who don't belong in America.’
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| 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".