Bibliographic record
Abstract
This chapter explores the powerful political motivations that inspired officials in Washington, regardless of political affiliation, to shape the post-9/11 and Iraq WMD contexts. The objective is to highlight the significant role leaders in the Democratic Party played in constructing public perceptions of the Iraq threat. Further, the significant bipartisan consensus that characterized relevant debates during this time period will reveal the power of prevailing perceptions regarding Saddam, Iraq, WMD, and ultimately the appropriate strategies for tackling such important foreign policy issues. Among the most relevant political speeches are those delivered by every prominent Democratic senator in October 2002 justifying their strong endorsement of the resolution authorizing the president to use ‘all necessary means’ to force Saddam’s compliance. The same group of senators would have been in power had Gore been elected president in 2000 and would have faced identical domestic pressures after 9/11 to craft similar speeches on Iraq. In fact, as noted earlier, the speeches read much like those delivered by many of the same senators in 1998 when voting 98–0 in support of the Iraq Liberation Act. There was really only one dominant perspective on the Iraq threat at the time, and neoconservatives were not relevant to establishing that standard point of view.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.042 | 0.006 |
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".