The Border Harms of Human Displacement: Harsh Landscapes and Human Rights Violations
Bibliographic record
Abstract
Building on the work of critical migration and border studies, particularly the scholarship on the suffering of displaced people through border-related violence, the article focuses on bordering practices and human rights violations relating to the Syrian civil war. It advances the argument that during peoples’ fragmented journeys to seek safety and protection within and outside of Syria, which are often punctuated by stops and starts, they encounter one or more of three kinds of bordering practices—hardening of borders, expansion of borders, and pushbacks—that can injure them and violate international human rights and often the principle of non-refoulement. The article refers to these encounters as the “border harms of human displacement”. The analysis emphasizes the experiences of people on the move and the cruelties and spatial violence they endure. The latter include lengthy periods of walking and running, travel across hazardous lands and seas, family separation, state restrictions, and mistreatment by border authorities. Yet, in response to such difficulties, they continue to assert their agency by negotiating bordering practices and harsh landscapes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| 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".