Center for Community Studies: Fourth Annual Current Issues Survey
Bibliographic record
Abstract
Country, state right direction/wrong track (2); importance of Canadian business and tourism (1); effect of tariffs (1); blighted/vacant property (4); low-income housing (1); news sources (4); visiting physician, healthcare access (4); New York State handling of recent strike by correctional officers at prisons (1); restricting smartphone use in K-12 schools (1); providing free breakfast and lunch to public school students (1); Medicaid for undocumented immigrants in NYS (1); free community college tuition in NYS (1); Advanced Nuclear Energy (2); approve/disapprove of President Donald Trump's handling of various issues (7); support/oppose various Trump proposals (3); importance of issues facing Northern and Central New York residents (3); Governor Kathy Hochul favorability (1); Trump favorability (1); presidential vote choice (2); military affiliation (1).
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 | 0.050 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.010 | 0.010 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".