Bibliographic record
Abstract
The alcohol ignition interlock is an in-vehicle DWI control device that prevents a car from starting until the operator provides a breath alcohol concentration (BAC) test below a set level, usually .02% (20 mg/dl) to .04% (40 mg/dl). The first interlock program was begun as a pilot test in California 18 years ago; today all but a few US states, and Canadian provinces have interlock enabling legislation. Sweden has recently implemented a nationwide interlock program. Other nations of the European Union and as well as several Australian states are testing it on a small scale or through pilot research. This article describes the interlock device and reviews the development and current status of interlock programs including their public safety benefit and the public practice impediments to more widespread adoption of these DWI control devices. Included in this review are (1) a discussion of the technological breakthroughs and certification standards that gave rise to the design features of equipment that is in widespread use today; (2) a commentary on the growing level of adoption of interlocks by governments despite the judicial and legislative practices that prevent more widespread use of them; (3) a brief overview of the extant literature documenting a high degree of interlock efficacy while installed, and the rapid loss of their preventative effect on repeat DWI once they are removed from the vehicles; (4) a discussion of the representativeness of subjects in the current research studies; (5) a discussion of research innovations, including motivational intervention efforts that may extend the controlling effect of the interlock, and data mining research that has uncovered ways to use the stored interlock data record of BAC tests in order to predict high risk drivers; and (6) a discussion of communication barriers and conceptual rigidities that may be preventing the alcohol ignition interlock from taking a more prominent role in the arsenal of tools used to control DWI. Whether interlock programs can help public policymakers achieve their expressed goals of substantially reducing the level of impaired driving will remain uncertain until procedural barriers and intransigent judiciary practices can be overcome that provide for more systematic routine use of interlock programs. Despite strong effectiveness evidence in all studies to date, the real potential of this technology to reduce the road toll cannot be estimated until they are more widely adopted.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".