Towards a New Kinship? Affective Engagements with Migrants Dead in the Mediterranean
Bibliographic record
Abstract
Between 2015 and 2018, Catania (Sicily) was one of the main arrival points for border crossers trying to reach the European Union without the necessary authorization from nation-states. A small group of locals involved with the Red Cross in migrant reception in the port decided in 2017 to organize themselves in order to find a way of “respecting” the dead border crossers arriving on European territory, alongside the living, during the search and rescue operations that have formed part of the landscape around the Mediterranean for several years. The idea of respecting the deceased turned into a project to develop a database aimed at providing a name and a biography for the unknown bodies buried in the local cemetery. The team succeeded in convincing the institutions involved in dealing with these bodies of the value of cooperating, which enabled them to consult the files held about the deceased by various police agencies and municipal institutions. Drawing on ethnographic material, we explore here an unexpected effect of the project. Our interlocutors – Red Cross volunteers, employees of the civil registry office, undertakers, forensic police officers – 97 who were all involved in constructing the database, and more broadly in dealing with the bodies, soon expressed an attachment to the deceased. In this essay, we aim to examine the social and emotional feelings of connectedness that are created through everyday acts, and sometimes quite trivial actions: visiting the dead in the cemetery, naming them, dreaming of them recurrently, or telling stories about them during family gatherings. Combining an ethnographic account of these relationships with anthropological scholarship on kinship, as well as on death studies, we intend to bring out some of the features of the new place created within Catania, and among some of its inhabitants, for border crossers who have died at sea.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".