Coco Chanel: Building an Empire – Chanel in Three Acts
Bibliographic record
Abstract
Abstract Shortly before the Second World War, a woman who had never accepted her orphan status, Gabrielle Bonheur Chanel, nicknamed ‘Little Coco’ by her father and known as ‘Coco’ to her relatives, became the first women in history to build a world-class industrial empire. By 1935, Coco, a fashion designer and industry captain, was employing more than 4,000 workers and had sold more than 28,000 dresses, tailored jackets and women's suits. Born into a poor family and raised in an orphanage, she enjoyed an intense social life in Paris in the 1920s, rubbing shoulders with artists, creators and the rising stars of her time. Thanks to her entrepreneurial skills, she was able to innovate in her methods and in her trendsetting approach to fashion design and promotion. Coco Chanel was committed and creative, had the soul of an entrepreneur and went on to become a world leader in a brand new sector combining fashion, accessories and perfumes that she would help shape. By the end of her life, she had redefined French elegance and revolutionized the way people dressed.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".