Bibliographic record
Abstract
This article considers two revenants – a man and a ghost – who haunt the Fann Psychiatric Clinic in Dakar, Senegal. Following Derrida’s assertion that haunting is historical, I take seriously the concept of haunting and insist upon its relevance to anthropological inquiry. As a mode of storytelling that comes from a particular way of apprehending the world, I argue that anthropology might give credence to specters as social figures and assign ethnography the task of chasing after ghosts, not simply for the poetic spaces they may open up but out of a concern for justice and responsibility in the past, present, and future. My own ethnographic encounter with the two revenants described here has generated questions about the often taken-for-granted equivalence of the real and the true. Likewise, it has encouraged me to interrogate the unpredictable (and oftentimes uneasy) cohabitation of memory and history, both within the Fann Clinic and beyond.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.028 | 0.051 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| 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".