National Security Education Program: Background and Issues
Bibliographic record
Abstract
The National Security Education Program (NSEP), authorized by the David L. Boren National Security Education Act of 1991 (NSEA, Title VIII of P.L. 102-183), provides aid for international education and foreign language studies by American undergraduate and graduate students, plus grants to institutions of higher education. The statement of purpose for the NSEA emphasizes the needs of federal government agencies, as well as the Nation's postsecondary education institutions, for an increased supply of individuals knowledgeable about the languages and cultures of foreign nations, especially those which are of national security concern and have not traditionally been the focus of American interest and study. Three types of assistance are authorized and currently provided by the NSEA: (1) David L. Boren Scholarships for undergraduate students to study in critical foreign countries; (2) grants to institutions of higher education to establish or operate programs in critical foreign language and area studies areas, including a National Flagship Language Initiative-Pilot Program; and (3) David L. Boren Fellowships to graduate students for education abroad or in the United States in critical foreign languages, disciplines, and area studies. Individuals who receive NSEP fellowships and scholarships are obligated for a limited period of time to seek employment in a national security position with a federal agency. Grant recipients who demonstrate that such positions are not available may fulfill the requirement through work in any federal agency or in the field of higher education in an area of study for which the scholarship or fellowship was awarded. The NSEP is intended to complement, and not duplicate, other federal programs of aid for foreign language and area studies education, such as those authorized under Title VI of the Higher Education Act and the Fulbright-Hays Act. This report provides background information on the NSEP and an analysis of related issues.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".