Remoteness and other risk factors in circumpolar road accident severity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Access to healthcare services is more challenging in remote northern regions due to higher travel costs associated with longer distances and harsh environments. Emergency response to road accidents in remote regions can take significantly longer than in more easily accessible locations, and potentially lead to more severe health outcomes. Accordingly, it is important to have insights on the factors that influence road accident severity in remote regions. This paper uses police accident data from Canada’s Northwest Territories between 1989 and 2019 to assess the influence of various factors on accident severity, including environmental, infrastructure-specific, geographical and accident-specific characteristics. Using multinomial logistic regression, we find that remoteness, off-road vehicle involvement and alcohol involvement increase the odds of a road accident being in a higher severity category. Overall, we find that risk factors that are more prevalent in Canada’s northern, remote regions may increase the severity of accidents in comparison to less remote regions.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it