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Record W4389205878 · doi:10.1080/17511321.2023.2277280

Book symposium on <i>Return of the grasshopper: games, leisure and the good life in the third millennium</i>

2023· article· en· W4389205878 on OpenAlexaff
Francisco Javier López Frías, Christopher C. Yorke, Filip Kobiela, Christopher Bartel, Gwen Bradford, Scott Kretchmar, J.S. Russell, William J. Morgan

Bibliographic record

VenueSport Ethics and Philosophy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsLangara College
Fundersnot available
KeywordsUtopiaEnvironmental ethicsSociologyArt historyHistoryPhilosophy

Abstract

fetched live from OpenAlex

Bernard Suits’ groundbreaking work, The Grasshopper: Games, Life, and Utopia, has profoundly shaped the philosophy of sport. Its sequel, Return of the Grasshopper: Games, Leisure, and the Good Life in the Third Millennium, released in October 2022, enriches scholarly understandings of Suits’ views on games, emphasizing the normative aspects of gameplay and its impact on people’s pursuit of the good life. In this book symposium, world-leading Suits scholars analyze the Suitsian conception of gameplay and its relevance to his views on Utopia outlined in the sequel, covering a wide range of topics. Filip Kobiela explores counterfactual situations in Suits’ oeuvre. Christopher Bartel and Gwen Bradford scrutinize the ethical nature and ramifications of Suits’ claim that life is an unconscious game. R. Scott Kretchmar and John S. Russell present thoughtful critiques of Suits’ musings on Utopia. William J. Morgan’s contribution integrates contemporary work studies to illuminate Suits’ utopia. The symposium concludes with the editors, Francisco Javier Lopez Frias and Christopher Yorke, offering their perspectives on Suitsian Utopia, ethics, and metaethics.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Commentary · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0230.005

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 head0.035
GPT teacher head0.299
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2023
Admission routes1
Has abstractyes

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