Bibliographic record
Abstract
The Zapotec culture (Oaxaca State, Mexico) is famous for its famous ‘funerary urns’, ceramic effigies associated with a vessel forming the body. Known since the beginning of the 19th century, these pieces have been the subject of iconographic studies which have, however, included numerous forgeries made as a result of their success. This particular production was the subject of doctoral research carried out by the author in the 1980s. It has made it possible to establish a typology and a history of the evolution of Zapotec forgeries (based on iconographic studies of collection pieces, comparisons with pieces from excavations and the use of thermoluminescence). Of the approximately 4,000 urns counted in the world (of which only 500 come from scientific excavations), and based on the study of about a thousand photos, we have been able to classify 330 pieces as fakes. Thus, extrapolating the total number of urns, we could suppose that more than a quarter of the known urns in the world are fakes or at least very dubious. Twenty-three varieties of forgeries have been identified, grouped into eleven ‘styles’. These groups seem to be characteristic of the periods during which they were made and the fashions from which they were inspired. Zapotec forgeries appeared at the beginning of the 20th century and reached their peak in the 1920s. It seemed to have disappeared by the 1930s. However, new considerations have led us to question the conclusion we proposed several decades ago and to consider a new production of fake urns during the 1950s and 1960s.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".