Beauty Competition in Central America: Zermat vs Avon
Bibliographic record
Abstract
In 2011, Avon commemorateci its 125th anniversary, and Zermat de Centroamerica (Zermat) its 20th. Two out of five women in 113 countries bought Avon’s beauty and related products. More than 80% of its $10.7 billion in sales were outside its North American division. Meanwhile, Zermat sold $30+ million in four Central American countries. Avon was the world’s largest direct seller, with 6.5 million independent sales representatives (mostly female), while Zermat’s 40,000 reps sold its products through 70+ distribution centers. Direct selling offered cost savings (i.e., fewer direct employees, lower advertising budgets and skipping payments to retailers for shelf space) and marketing advantages (i.e., sales reps with the support of catalogs communicate, promote and earn the loyalty of their customers). These advantages have allowed direct sellers to charge lower prices than those of competitors selling through retailers, thus creating an image of good value.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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 teacher head, 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".