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Record W4288721953 · doi:10.5281/zenodo.6932651

Play to Lose: Animation, Failure, and the Milieu in Trophy Dark

2022· paratext· en· W4288721953 on OpenAlexaff
Eric Stein

Bibliographic record

VenuePhilPapers (PhilPapers Foundation) · 2022
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsTrinity Western University
Fundersnot available
KeywordsTrophyAnimationComputer scienceComputer animationComputer graphics (images)GeographyArchaeology

Abstract

fetched live from OpenAlex

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 <em>Trophy Dark</em> (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 <em>Dungeons &amp; Dragons</em> (and solely <em>Dungeons &amp; Dragons</em>) and students with no tabletop roleplaying experience whatsoever, <em>Trophy Dark</em>, 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 <em>Trophy Dark</em> 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 <em>Trophy Dark</em>'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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.573
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.008

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.

Opus teacher head0.016
GPT teacher head0.226
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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