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Record W4380928484 · doi:10.3138/ctr.131.003

Bridging Opposites – Drama and Science – in the Plays of John Mighton

2007· article· en· W4380928484 on OpenAlexvenueaboutno aff
Christopher Innes

Bibliographic record

VenueCanadian Theatre Review · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsnot available
Fundersnot available
KeywordsDramaPerformance artMythologyTheatre directorArt historySociologyArtVisual artsLiterature

Abstract

fetched live from OpenAlex

In terms of drama that deals with science, the award-winning Canadian playwright John Mighton is almost unique in being a practising scientist as well as a professional playwright. Indeed, he holds two PhD degrees: one in philosophy and one in mathematics. He has published a highly regarded book on mathematics, under the title of The Myth of Ability, and is the founder and coordinator of a highly innovative school program designed to help students who are having difficulty with math, called JUMP (which stands for “Junior Undiscovered Math Prodigies”). He has also written six plays to date, which have been staged widely across Canada as well as being performed in Europe, Japan and the United States. One of these, Possible Worlds, has been turned into a film by the Canadian director Robert Lepage; and Mighton is currently working with Lepage again, adapting for the stage a science book, titled The Elegant Universe: Superstrings, Hidden Dimensions and the Quest for the Ultimate Theory – a title that demonstrates the ambitiousness of Mighton’s aims. He has also won a number of prestigious national prizes, including no fewer than two Governor General’s Awards for Drama. And, in 2006, he was awarded the Siminovitch Prize (the most prestigious and valuable theatre award in Canada).

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.276
Threshold uncertainty score0.549

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.014
Scholarly communication0.0090.006
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.038
GPT teacher head0.292
Teacher spread0.254 · 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
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

Citations0
Published2007
Admission routes2
Has abstractyes

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