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Record W2884214381 · doi:10.22215/etd/2018-12937

“Making a Business of Good Taste”: Minerva Elliot and the Professionalization of Interior Decoration in Toronto, 1925 – 1939

2018· dissertation· en· W2884214381 on OpenAlexaboutno aff
Nicola Krantz

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsnot available
Fundersnot available
KeywordsInterior designProfessionalizationTasteBiographyIdentity (music)Visual artsMaking-ofEngineeringMedia studiesSociologyArt historyHistoryArtManagementAestheticsSocial sciencePsychology

Abstract

fetched live from OpenAlex

This thesis examines the development of the interior decorating profession in Toronto by following the career trajectory of interior decorator Minerva Elliot (1887-1964). Elliot's biography allows entry into spaces of inquiry beginning with the T. Eaton Company in Toronto as a site of education for its clientele and the emerging professional. Additionally, the upscale decorating magazine Canadian Homes and Gardens serves as an important tool for providing evidence of Elliot's independent practice, featuring her decorating advice and illustrations of her work. This thesis explores how the department store and magazine helped to professionalize the field of interior decoration, which dealt with various modern tastes in Toronto's evolving metropolis. I argue that interior decoration - and Minerva Elliot's voice alike - occupies an important and overlooked part of Canadian design and women's history, and draws attention to the significance of interior decoration as a means of expressing identity in interwar Toronto.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.564

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0250.017
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
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 head0.025
GPT teacher head0.285
Teacher spread0.261 · 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
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
Published2018
Admission routes1
Has abstractyes

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