Fairleigh Dickinson University's PublicMind: New Jersey November 2015 Poll
Bibliographic record
Abstract
Reside in New Jersey (1); registered to vote (1); President Barack Obama job approval (1); country right direction/wrong track (1); New Jersey Governor Chris Christie job approval (1); New Jersey right direction/wrong track (1); trust which major political party in New Jersey more (1); pay inequity between men and women (2); presidential candidate matchups (4); favorability of New Jersey political figures (8); increase in state gasoline tax (4); purchase Jersey Fresh or locally grown fruits and vegetables (3); Canada geese (2); funds for preserving open spaces used for other environmental causes (1); favor raising amount of money not touched by estate tax (1); have a tattoo (1); body piercings other than ears (1); acceptable to wear facial jewelry at work (1); vote for Republican presidential candidates (1); vote for Democratic presidential candidates (1); miles driven each day (1); public employee pension system membership (1); Fairleigh Dickinson University (2).
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.031 |
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".