Critical Infrastructure Protection: DHS Efforts to Assess Chemical Security Risk and Gather Feedback on Facility Outreach Can Be Strengthened
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "Since 2007, the Department of Homeland Security's (DHS) Infrastructure Security Compliance Division (ISCD) has assigned about 3,500 high-risk chemical facilities to risk-based tiers under its Chemical Facility Anti-Terrorism Standards (CFATS) program, but it has not fully assessed its approach for doing so. The approach ISCD used to assess risk and make decisions to place facilities in final tiers does not consider all of the elements of consequence, threat, and vulnerability associated with a terrorist attack involving certain chemicals. For example, the risk assessment approach is based primarily on consequences arising from human casualties, but does not consider economic consequences, as called for by the National Infrastructure Protection Plan (NIPP) and the CFATS regulation, nor does it consider vulnerability, consistent with the NIPP. ISCD has begun to take some actions to examine how its risk assessment approach can be enhanced, including commissioning a panel of experts to assess the current approach, identify strengths and weaknesses, and recommend improvements. ISCD will need to incorporate the various results of these efforts to help them ensure that the revised risk assessment approach includes all elements of risk. After ISCD has incorporated all elements of risk into its assessment approach, an independent peer review would provide better assurance that ISCD can appropriately identify and tier chemical facilities, better inform CFATS planning and resource decisions, and provide the greatest return on investment consistent with the NIPP."
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 | 0.023 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.075 | 0.017 |
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".