Imagining an (Un)productive Anthropology Through The Night
Bibliographic record
Abstract
Through this email exchange, we have tried to engage with ourselves by considering our bodies as archives of trauma, feelings, and ideas, using the thematic of the nighttime and nightness. Nightness emerges as a counter epistemology in our rumination and it transfigures the dualisms of day and night, productive and unproductive as merging in space and time. By writing ourselves as bodies of the night, such that we belong both to the day and to the night, or perhaps neither to the day nor to the night, we use the night and nightness to process our grief; to feel grief and to escape away from it into a possibility of thinking/feeling where we exist and we don’t at the same time. These emails not only suggest a counter epistemology but also the possibility of an (un)productive anthropology, one which happens within each of us around nightness - away from the day, or rather, away from the neoliberal expectation of the day.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.033 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".