Bibliographic record
Abstract
Abstract : Throughout his presidential campaign and again as recently as the 2010 State of the Union address, Pres. Barack Obama reinforced his commitment to lift the ban on homosexuals serving openly in the US military. Although he cannot lift the ban on his own--only the legislative branch has that authority--the president's clear stance and the Democratic Party's majority in Congress point to a repeal of the Ask, Don't Tell (DADT) policy in the nearer term. In fact, a bill has already been introduced, and some Democrats in Congress are posturing to include a repeal in their versions of the defense authorization bill this year. Moreover, in congressional testimony, Adm Michael G. Mullen, chairman of the Joint Chiefs of Staff (JCS), stated that it was his personal belief that allowing gays and lesbians to serve openly would be the right thing to do. These facts make a repeal of DADT more likely than not--therefore, the Department of Defense (DOD) should begin preparing now to manage prospective impacts to its forces. The US military, with its ban on the open display of homosexuality, stands with 11 other countries, but this list does not include countries where homosexuality is banned outright, such as Iran, Saudi Arabia, and several other nations in the Middle East. However, other key allies, including the United Kingdom, Canada, Australia, and Israel, have already lifted the ban on homosexuals serving in their militaries. In fact, 24 foreign militaries now have no ban on gay service members, and many of these allies provide support to the North Atlantic Treaty Organization (NATO) International Security Assistance Force in Afghanistan. These combat-tested fighting forces are critical partners in the American defense strategy and can provide insight to the United States as it prepares for its own policy change regarding homosexuals.
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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.095 | 0.029 |
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".