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Record W2793720268

Costume culture: a traveling exhibition system for the Costume Museum of Canada

2014· dissertation· en· W2793720268 on OpenAlexaboutno aff
Deniz Özge Aytaç

Bibliographic record

VenueMspace (University of Manitoba) · 2014
Typedissertation
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionCostume designArtVisual arts
DOInot available

Abstract

fetched live from OpenAlex

The Costume Museum of Canada (CMC) is the first of its kind in Canada. It works as a comprehensive repository where Canadian clothing and textile artifacts are collected, preserved, and presented. Traveling exhibits are important to the CMC to present the collection to a wider audience; however, the CMC’s financial limitations restrict how they can support traveling exhibitions. This practicum project addresses the desire of the museum for a facility to stage traveling exhibits by the design of a Traveling Exhibition System (TES) for the CMC. The practicum explores the concepts of cultural communication, narratology and mise-en-scene. It will facilitate Canadian cultural education through the exhibition of CMC’s vast collection of costumes and related accessories in a cost effective and sustainable manner. TES will be an exhibit system that can be set up within existing buildings and spaces. The project offers the possibility for the CMC to generate revenue and to facilitate dissemination of Canadian fashion culture and history regionally and nationally.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.129
Threshold uncertainty score0.260

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0300.003

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 head0.018
GPT teacher head0.181
Teacher spread0.164 · 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
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

Citations1
Published2014
Admission routes1
Has abstractyes

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