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Record W6959890136 · doi:10.11575/prism/40601

Hookman: Finding Meaning in the Fragments

2023· other· en· W6959890136 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2023
Typeother
Languageen
FieldSocial Sciences
TopicHistorical Geography and Cartography
Canadian institutionsnot available
Fundersnot available
KeywordsFluencyStorytellingCompetence (human resources)Statement (logic)Meaning (existential)Focus (optics)

Abstract

fetched live from OpenAlex

This artist statement is meant to demonstrate competence and fluency in theatrical scenic and lighting design. The design elements explored in this thesis were created for a production of Lauren Yee’s play Hookman, directed by Jenna Rodgers and presented in the Reeve Theatre at the University of Calgary from October 21st – October 29th, 2022. This is an exploration of the artistic collaborative processes used on Hookman from the initial conceptual design phase to the fully realized production using iterative design processes and collaborative frameworks with a focus on storytelling through scenic and lighting design. Further, this is a reflection on the specific lessons learned throughout this process with an eye towards future research inspiration, developing questions for further reflection.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.002

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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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 designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

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