Bibliographic record
Abstract
An oil pumpjack, erected on the edge of a McDonald’s parking lot, is front and centre. Visible just behind the jack are the colourful letters designating the restaurant’s Playspace, while off to the left is the globally-recognizable double arch of the fast food empire’s sign. In Alberta, where I grew up, the pumpjack is not an unfamiliar sight. But this was the first time I had seen a fake pump jack, and the first time, too, that I had seen anything like it near the golden arches. So why a pumpjack here in Edmonton? And why this fake approximation of the real thing - a child’s version of the complex mechanical apparatus found on oil fields around the world? This pumpjack moves, up and down, slowly and patiently pretending to carry out the work that it has to do. This McDonald’s isn’t hidden away, but is located at the corner of two major arteries, one running across the city and the other into and out of it. Thousands of commuters move past both daily, as do visitors rushing from the core to the airport. In an otherwise drab and ugly part of Edmonton (though there are many such parts) made up of little more than chain stores and light industry, the pumpjack stands out, a strange sentinel. Its very existence seems to insist on its importance and necessity. Yet even so, its presence at McDonald’s domesticates it, making it an object safe for everyday life.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.108 | 0.020 |
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".