Border Security Technologies: Local and Regional Implications
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
Abstract The Bush administration's “Smart Border” accords with Mexico and Canada present a number of important implications for North America's border communities and regions. As part of the plans, new security technologies have emerged as the preferred policy solution to the difficult problem of screening for weapons and terrorist incursions into the United States through its international boundaries while maintaining flows of goods and individuals, key drivers of globalization and hallmarks of the North American Free Trade Agreement (NAFTA) era. These new technological systems have various capabilities, ranging from prescreening cargo to identifying problematic travelers to detecting nuclear material in trucks. Deploying these systems in border communities, however, invokes a range of important economic, social, and political challenges, all of which are under examination in this work. Using a risk‐centered approach to United States border security, this article explores several technologically oriented border control systems: screening, biometrics, and information technology. The research is based on regional field research and a public policy analysis method that uses Birkland's “focusing event” framework, a model that provides insights into the postcrisis policy formation process. The article concludes by offering an initial appraisal of these policies within the context of risk, interdependent border communities, and an open democratic society.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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