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Fifty Years of <i>Dungeons &amp; Dragons</i>

2024· book· en· W4392214597 on OpenAlexaboutno aff

Bibliographic record

VenueThe MIT Press eBooks · 2024
Typebook
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

On the fiftieth anniversary of Dungeons &amp; Dragons, a collection of essays that explores and celebrates the game's legacy and its tremendous impact on gaming and popular culture. In 2024, the enormously influential tabletop role-playing game Dungeons &amp; Dragons—also known as D&amp;D—celebrates its fiftieth anniversary. To mark the occasion, editors Premeet Sidhu, Marcus Carter, and José Zagal have assembled an edited collection that celebrates and reflects on important parts of the game's past, present, and future. Each chapter in Fifty Years of Dungeons &amp; Dragons explores why the nondigital game is more popular than ever—with sales increasing 33 percent during the COVID-19 pandemic, despite worldwide lockdowns—and offers readers the opportunity to critically reflect on their own experiences, perceptions, and play of D&amp;D. Fifty Years of Dungeons &amp; Dragons draws on fascinating research and insight from expert scholars in the field, including: Gary Alan Fine, whose 1983 book Shared Fantasy remains a canonical text in game studies; Jon Peterson, celebrated D&amp;D historian; Daniel Justice, Canada Research Chair in Indigenous Literature and Expressive Culture; and numerous leading and emerging scholars from the growing discipline of game studies, including Amanda Cote, Esther MacCallum-Stewart, and Aaron Trammell. The chapters cover a diverse range of topics—from D&amp;D's adoption in local contexts and classrooms and by queer communities to speculative interpretations of what D&amp;D might look like in one hundred years—that aim to deepen readers' understanding of the game.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.608
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.291
Teacher spread0.251 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2024
Admission routes1
Has abstractyes

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