Bibliographic record
Abstract
This research-creation project, part of the DE\GLOBALIZE artistic research cycle, investigates the complexities of Congo violence, care, and colonialism. Drawing on Michel Serres' metaphor of the great estuaries, the study explores the topology of interactive documentaries, blending theory, emotion, and personal experiences. Accessible through the interactive web documentation at http://deglobalize.com, the platform offers a media-archaeological archive for speculative ethnography, enabling the forensic processing of single documents in line with actor-network theory. Focusing on the ambivalence of violence and care, the field trip to the Congo in March 2022 involved collaboration with local artists and was based on a postcolonial reflection from 1996. The outcome, a 30-minute autoethnographic essay titled Inner Congo, reflects on inner violence and its connection to colonialism, transcending the dichotomy between art and science. The study examines political, technological, and psycho-geographic borders, engaging with local communities to interrogate the displaced consumption of resources, ghost acreages, and self-lies. Informed by the works of Achille Mbembe and Franz Fanon, the research confronts the foreign, the dark, and the displaced ghosts within the participants. DE\GLOBALIZE is problematized as an example of epistemic violence for the ethnographic memory of (Western) knowledge. The study emphasizes the importance of caring for the sensitivity of the researchers' skin, the g/hosts, and mother earth. The encounters in the Congo reveal the palpable legacy of violence and the continued exploitation in post-colonialism. The Art Academy and the Mission Station serve as both havens for wounded souls and witnesses of a bloody European heritage. In Isiro, the researchers confront their own greed when meeting Trésor, a mine owner with 6,000 workers digging for gold. Violence constantly finds new ground, with totalitarian folds increasing in our psyches. Inspired by Sven Lindqvist's Gräv där du står (1978), the research emphasizes the need to face our brutality and demons through symbols and calculations that protect yet disenchant us simultaneously. Inner Congo offers a poignant and immersive exploration of the complexities of violence in the Congo, unearthing hidden narratives and inspiring critical reflection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.004 |
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".