Bibliographic record
Abstract
Over the course of 23 years, United States Senator Susan Collins (R-ME) has been able to successfully walk a unique line of nonpartisanship, never stepping too far to the right, or to the left. However, following her vote to confirm Justice Brett Kavanaugh to the United States Supreme Court in 2017, and her vote to acquit President Trump of his impeachment charges in early 2020, Susan Collins placed herself in an incredibly precarious situation. Pundits and analysts were convinced that this election would turn into a referendum on Susan Collins (Lyall 2020). Meanwhile, her opponent, the current Speaker of the Maine House of Representatives, Sara Gideon, consistently led in the polls and worked off of the momentum gained from the success of the U.S. House Democrats in the 2018 midterms. And yet, Susan Collins stunned the nation by defeating Gideon. This paper evaluates and analyses what possible causes led to this outcome. Ultimately, Collins’ choice to vote against the confirmation of late-Ruth Bader Ginsburg's replacement on the Supreme Court convinced Mainers that Susan Collins could still be trusted, and should be given another chance.
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 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 | 0.003 | 0.008 |
| 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 | 0.000 |
| 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 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".