Bibliographic record
Abstract
1 Such redistricting is required by the constitutional principle of one person/one vote announced by the United States Supreme Court in Wesberry v. Sanders, 376 U.S. 1 (1964) and Reynolds v. Sims, 377 U.S. 533 (1964).2 New York Common Cause, Comments by Common Cause/NY to the Senate Standing Committee On Election, (Oct.9, 2009), http://www.commoncause.org/policy-and-litigation/testimony/NY_101209_Comments_Election_Reform_Senate.pdf("Common Cause/New York is a nonpartisan citizens' lobby and a leading force in the battle for honest and accountable government.Common Cause fights to strengthen public participation and faith in our institutions of self-government and to ensure that government and political processes serve the general interest, and not simply the special interests.")."Can the Plan": How the 2012 Redistricting Deal Denies New Yorkers Fair Representation and the Fundamentally Flawed Redistrcting "Reform", NYPIRG (June 2014), http://www.nypirg.org/pubs/goodgov/2014.06.23Redistricting-CanthePlan/cantheplan.pdf."Consonant with our overall mission we have consistently worked . . . to improve accessibility, accuracy, transparency, and verifiability in our democratic process at the city, state and national level."Testimony of Susan Lerner Executive Director, Common Cause/
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.017 | 0.008 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".