Bibliographic record
Abstract
Editor—Analyse the assumptions that drivers make when they complain about road safety campaigns and you must conclude that drivers believe that they and their business are inherently more important than the lives of anyone on foot. There is no other explanation for their attitudes. Scratch a driver and you find someone who really believes—perhaps without even realising it—that he or she has the right to kill people who happen to be in the wrong place at the wrong time. How else do you explain the way that one acquaintance told me about a neighbour's recent experience? The neighbour had turned too fast around a corner and run into two young girls on a crossing. One was killed, the other badly injured. “Poor chap,” said the man. “He didn't stand a chance.” No thought of the chances of the children in the neighbour's path. You can be certain that he faced a fine and that the girls' parents wished they had got away as lightly. This is a British problem. Walk around Vancouver, or Detroit, or even southern Portugal and most drivers will let you cross the road they are turning into—as is still provided by law in the United Kingdom but universally ignored. Drivers in these and other places tend to treat people on foot as no different from themselves. Perhaps as a legacy of the days when the gentry drove round in carriages, generations of British schoolchildren have been indoctrinated to defer to drivers. If they so much as hear a car, they are told, they should wait until it goes by. The lesson is that the police and others who indoctrinate children this way are not teaching pedestrians, they are teaching tomorrow's drivers. When these children pass their driving tests they expect to inherit a level of abjection no civilised society should tolerate. Surely drivers who don't accept a duty of care to other road users and who drive without regard for the safety of others are unwell, whatever the medical term. If you doubt this, think what would happen if they acted similarly in any context other than a conflict between driver and pedestrian or cyclist. It is a matter that needs to be emphasised in the BMJ because, whatever the (under-reported) statistics tell us, the undeclared war on child and other pedestrians is sapping the NHS of resources and inflicting untold grief among the rest of us.
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 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.018 |
| Insufficient payload (model declined to judge) | 0.028 | 0.019 |
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".