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Record W2883504706 · doi:10.22329/wyaj.v35i0.5110

Calvinball: Users’ Rights, Public Choice Theory and Rules Mutable Games

2018· article· en· W2883504706 on OpenAlexvenueno aff
Bob Tarantino

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsnot available
Fundersnot available
KeywordsRhetoricMetaphorPoliticsNormativeNarrativeLaw and economicsMetagamingNorm (philosophy)SociologyGame studiesDisadvantagedPolitical scienceComputer scienceAestheticsMedia studiesLawGame theorySequential gameEconomicsArtSimultaneous gameLiteraturePhilosophyMathematical economicsLinguistics

Abstract

fetched live from OpenAlex

This article proposes the “rules mutable game” as a metaphor for understanding the operation of copyright reform. Using the game of Calvinball (created by artist Bill Watterson in his long-running comic strip Calvin & Hobbes) as an illustrative device, and drawing on public choice theory’s account of how political change is effected by privileged interests, the article explores how the notion of a game in which players can modify the rules of the game while it is being played accounts for how users are often disadvantaged in copyright reform processes. The game metaphor also introduces a normative metric of fairness into the heart of the assessment of the copyright reform process from the standpoint of the user. The notion of a rules mutable game tells us something important about the kinds of stories we should be telling about copyright and copyright reform. The narrative power of the “fair play” norm embedded in the concept of the game can facilitate rhetoric which does not just doom users to dwell on their political losses, but empowers them to strategize for future victories.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.044
GPT teacher head0.272
Teacher spread0.228 · 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
GenreEmpirical

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

Citations1
Published2018
Admission routes1
Has abstractyes

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