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Cutting a Fashionable Fit: Dressmakers' Drafting Systems in the United States

2007· article· en· W6931549551 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSmithsonian Digital Repository (Smithsonian Institution) · 2007
Typearticle
Languageen
FieldMedicine
TopicRenin-Angiotensin System Studies
Canadian institutionsnot available
Fundersnot available
KeywordsClothingVariety (cybernetics)Quarter (Canadian coin)Clothing industryStyle (visual arts)

Abstract

fetched live from OpenAlex

The first dressmakers' drafting system was created in the United States before 1838. This innovation provided a tool to draft stylish, fitted garments and appealed to women who were forced to make their own clothes. The concept behind the first generation of drafting systems was used as the basis for the sizing systems in the paper pattern industry and the women's ready-made clothing industry. In the last quarter of the 19th century, hundreds of drafting systems were invented to help the professional dressmaker cut the complex patterns of the fashionable dress of the period. A wide variety of changing economic, social, and technological factors determined the methods that were created at specific times, how the systems were sold, and who used them. Dressmakers' drafting systems with specialized tools became obsolete in the 20th century after simpler, less fitted dress styles became popular. These less complicated fashions encouraged the widespread acceptance of ready-made clothes and the use of paper patterns by dressmakers and home sewers.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.278
Teacher spread0.250 · 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