An Infrastructure of Grief: Border Imaginaries and Perspectives Gathered from a Journey Along the Route of the Real and Imagined Texas-Mexico Wall
Bibliographic record
Abstract
This article explores the effects of the border wall between the US and Mexico, from the perspectives of people living along it and through careful consideration of its effects on non-human persons. Two doctoral students travel 400 miles along the Rio Grande River, examining relationships to place in the US-Mexico borderlands through interviews with DACA recipients and their lawyer, environmentalists, and local hikers. Critical place inquiry foregrounds place as a methodology. Racial melancholia provides a framework for understanding how the border is imagined as necessary for the continuation of the settler colonial project, despite costs to diverse forms of life. Conclusions explore the nonsensical nature of the project of building a wall, the resistance to being categorised as static, and the physical and psychic violence caused by the restriction of movement.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.020 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".