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Record W4405834647 · doi:10.1386/scp_00122_7

Jumping off a cliff: In conversation with Shawn Kerwin

2024· article· en· W4405834647 on OpenAlex
Marlis Schweitzer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueStudies in Costume & Performance · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicCrafts, Textile, and Design
Canadian institutionsYork University
Fundersnot available
KeywordsCliffConversationEngineeringLinguisticsGeographyPhilosophyArchaeology

Abstract

fetched live from OpenAlex

This conversation with award-winning Canadian designer Shawn Kerwin explores the need for emerging designers to embrace risk and create their own opportunities for learning and professional development. Kerwin has designed sets and costumes for theatre for over forty-five years and has taught at the post-secondary level for over twenty-five. Her design work has been on stages across North America and across the world. While she holds a passion for opera and the classic repertoire, she has also been involved in numerous world premieres of plays and opera. As a teacher, she is passionate about helping students find their own creative voice and introducing them to the work of Canadian playwrights, many of whom she has had the pleasure of working with on new scripts. Over the past two years, in collaboration with the Charlottetown Festival and other organizations, she has mentored numerous young designers as they make the transition from being a student to becoming an active professional. She is currently exploring virtual costume design in an ongoing effort to continue learning and building her own skills.

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.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.571

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.093
GPT teacher head0.305
Teacher spread0.212 · 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