Journeys and landscapes of forced migration: Memorializing fear among refugees and internally displaced Colombians
Bibliographic record
Abstract
In Colombia, a country with a long‐standing multipolar armed conflict, the performance of violence in the form of massacres, selective assassinations, threats, disappearances, rape and forced displacement has turned fear into a powerful language by which the various armed actors communicate with society, reconfigure the landscape and regulate everyday life. Understanding forced migration as a form of displacement under coercion and fear, this article examines forms and notions of memorialized fear that are inscribed in the narratives of displacement and exile of a group of internally displaced persons (IDPs) in Colombia and Colombian refugees in Canada. The article explores the relationships between memory, fear, and forced migration as a means to advance an anthropological analysis of the ways people reconstruct their lives in the midst of displacement and change. I suggest that a continuum of fear marks the journeys of displacement and exile of Colombian forced migrants. Fear is expressed as embodied memory and narrative thread to remember the past, the journey of forced migration, the interactions with the forced migration regime and the arrival and experiences in another host society. In the context of change and the liminal situations of IDPs and refugees, I consider the weight of emotions such as fear in shaping experience and remembrance so as to offer a critical starting point in reconsidering approaches towards, and conceptualizations of, identity, re‐establishment of rights and incorporation into new social 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.008 |
| 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".