Bibliographic record
Abstract
Thursday, 11 August 2005. Killing time, I visit the Museum of Tolerance in Los Angeles. This is coming to the end of a tour of the Arthur Murray dance studios up and down the West Coast. It is a hot break coming at the end of a month’s dance fieldwork in Sacramento. Rather than fly back to Belfast from San Francisco, I opted for LAX and bookended my research with a personal journey driving up and down the state. I had gone up through Death Valley where I had solo hiked into the desert and made a souvenir vial of Death Valley sand. Then inland north to get through Yosemite, living in my rental car, sleeping in motels. Back south, I was sampling the dance studios along the coast—waltz in San Francisco, rumba in Hayward, foxtrot in Redwood City, tango in San Jose, salsa in chic Santa Barbara, merengue in Beverley Hills. Along the way, I was taking in the tourist attractions: the boardwalk in Santa Cruz where the movie Lost Boys was filmed; Cannery Row, Monterey, described long ago by John Steinbeck; Hearst Castle, which had inspired Orson Welles’s Citizen Kane.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.195 | 0.059 |
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".