Intensity and uncertainty: Performing border conflicts at the US–Mexico borderlands
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
Abstract This article draws on border studies that recognise rebordering practices as ongoing performances of conflict between various actors including state authorities, border security agents, migrants, migrant supporters, smugglers, international organisations, lawyers, advocates and others. We draw attention to variable levels of intensity with which these conflicts are performed and the impact they have on migrants' ability to exercise their agency. We understand intensity to mean not merely the emotional discursive environment in which these conflicts unfold, and the pressure tactics used by at least some parties, but, more importantly, the speed of the responses by all actors involved in this border performance. Focusing on rebordering practices at the US–Mexico borderlands in 2018 and 2019 adopted in response to new forms of mobility, we characterise these years as a period of high intensity, when rapidly changing policies provoked immediate responses by migrants, and equally speedy counter‐responses by other actors, particularly the US and Mexican administration. We suggest that the volatile architecture of border control in the US–Mexico borders has rendered many strategies employed by Central American migrants to overcome obstacles and create innovative solutions virtually ineffective. The article is based on an ethnographic study carried out between early May and mid‐August 2019 in Mexico.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it