Consensus Statements on the Assessment of Older Drivers
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
BACKGROUND: The rapidly increasing number of older drivers is accentuating the challenges in concurrently identifying older drivers posing an unacceptable risk if they continue to drive, while not discriminating against those capable of safely driving. Attendees of an invitational meeting about the assessment of older drivers were asked to participate in a modified Delphi process designed to develop consensus statements on the assessment of older drivers. METHODS: Forty-one non-student symposium attendees were invited to participate in two rounds of a survey, in which they were asked to indicate their level of agreement (or disagreement) on a five-point Likert scale to a series of statements about the assessment of older drivers. Consensus was defined as 80% + of respondents either agreeing or disagreeing with a statement. RESULTS: More than one-half (n = 23) completed the first round of the survey and 12 participated in the second. There was consensus on the need for a modifiable, fair, rational, and widely accessible multi-step approach to the assessment of older drivers. This would require the engagement and support of physicians and other health-care practitioners in identifying and reporting medically at-risk drivers of any age. At a societal level, alternatives to driving a personal motor vehicle should be developed. CONCLUSIONS: An on-going dialogue about this complex issue is required. Decisions should be based on explicitly stated principles and informed by the best available evidence.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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