Bibliographic record
Abstract
This paper describes how the Traffic Injury Research Foundation has undertaken the creation of an international inventory of ignition interlock programs. This international resource is designed to provide current information about interlocks to researchers and practitioners working in this field, and also to those individuals and agencies who are considering, developing, or undergoing program implementation. The primary goals of this paper are to provide guidance to jurisdictions aiming to develop and implement programs, identify research needs and opportunities, share information, and facilitate ongoing initiatives by providing current, easily accessible sources of information, data, and contacts. The development of this inventory began with a comprehensive interlock survey that was designed to capture information relating to key program features, administrative and monitoring data, operational details, participating agencies and program contacts. Jurisdictions included in the survey were Australia, Canada, Europe and the United States. Supporting legislation for programs was also gathered with the assistance of the National Traffic Law Center, the National Conference of State Legislators, and program administrators. To date, completed surveys have been received from most jurisdictions in Australia, Canada, and Europe. Information has been gathered from a significant number of States as well; however, information from some jurisdictions is still lacking. Survey information was most difficult to collect from those states where their interlock programs were supervised by courts and probation, mainly because practices vary across counties, making it necessary to contact multiple courts and probation officers to gather statewide information. As this project progressed, it became apparent that many jurisdictions were in the process of developing or implementing an interlock program, or revising an existing program, meaning that any technical report produced would be rapidly outdated before it could be published. Information about interlock programs was constantly changing as programs were being added, expanded, and improved.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.031 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".