Issues Pertaining to Rebuilt Vehicle Titles
Bibliographic record
Abstract
In Kentucky, salvage titles are issued when a vehicle has been wrecked, destroyed, or damaged and the cost of repairs exceeds 75 percent of the vehicle’s fair market value. Once a vehicle is repaired to roadworthy condition it is issued a rebuilt title. Kentucky issued 110,000 rebuilt and salvage titles in 2018. Over the 2014 to 2018 period, the number of rebuilt and salvage titles issued climbed 31 percent. The economic impact of rebuilt and salvage titles in Kentucky is considerable — approximately $331 million in 2018, based on data for the taxable values or sales prices of vehicles. To document titling practices for rebuilt and salvage vehicles adopted by other agencies, the Kentucky Transportation Center (KTC) distributed a survey to all American states and Canadian provinces and territories. From it, researchers learned that Ohio has a very robust inspection program for rebuilt and salvage vehicles. The survey and interviews with Ohio personnel revealed that other states have persistent concerns about Kentucky’s rebuilt and salvage titles. In particular, some states do not accept Kentucky’s red titles (rebuilt and salvage vehicles that were transferred into Kentucky). Ohio inspectors have identified multiple stolen vehicles that had been titled as rebuilt or salvage in the Commonwealth. To improve the rebuilt and salvage vehicle titling process, state administrators in the Division of Motor Vehicle Licensing could consider implementing a program similar to Ohio’s in terms of technology, workflow and the inspection cost assessed to individuals or businesses wishing to obtain a rebuilt or salvage title.
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 | 0.014 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".