Bibliographic record
Abstract
The day of the last live auction at Sotheby’s in the spring of 2020 was on 19 March 2020 as multiple coronavirus lockdowns forced auction rooms to close worldwide. In the following months, hundreds of live auctions were cancelled or postponed, and combined revenue at Christie’s, Sotheby’s, and Phillips for the second Quarter 2020 plummeted 79% year on year from USD 4.4 bn in Q2 2019 to USD 0.9 bn in Q2 2020. This article focuses on public auctions at Christie’s, Sotheby’s, and Phillips and uses primary research to demonstrate how leading auction houses responded to the unprecedented challenges posed by the COVID-19 crisis. Leveraging Pi-eX’s public auction results database and its 12-month-rolling methodology, our analysis shows (1) the surge of online only auctions while the number of live auctions plummeted; (2) the limitations of online only auctions and the rise of new opportunities; and (3) a comparison of the COVID-19 crisis with previous art market crisis in the past 15 years.
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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".