Bibliographic record
Abstract
In her essay "Reclaiming Animism" (2012), Isabelle Stengers writes that reclaiming "means recovering, and, in this case, recovering the capacity to honor experience, any experience we care for, as 'not ours' but rather as 'animating' us, making us witness to what is not us." It is this notion of animation that mobilizes this paper on Jesse Ross's tabletop roleplaying game Trophy Dark (2021), and which informed my own experience as simultaneous game facilitator and game design instructor for a class of fifteen undergraduate students. With a group split roughly in half between students with varying levels of experience with Dungeons & Dragons (and solely Dungeons & Dragons) and students with no tabletop roleplaying experience whatsoever, Trophy Dark, and specifically Ross's incursion "Witchwood," made for a group exercise in this animative witness to the "not ours" and "not us" of which Stengers writes. Rather than adopting a rationalist, critical separation from the play experience, or a romantic, reflective immersion in the play experience, this particular group of students discovered in Trophy Dark a vehicle for the "active," "transformative," and indeed "metamorphic" experience that Stengers describes, using the chosen incursion as an instrument for the shared dramatic failure that is "playing to lose," as advocated in Trophy Dark's player's guide. Stengers awakens her readers to a "rhizomatic" materialism, or a materialism of the "milieu," and together in the Witchwood we encountered the same. This paper charts the contours of our adventure.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".