New York City collects nearly a billion in fines last year
Bibliographic record
Abstract
New data shows that New York City made a record $993 million from fine payouts last year. Total fines were up by nearly 4 percent, with officials handing out nearly 700,000 quality of life fines. The city of New York is cleaning up...on fines...A new reports shows it made a record $993 million from fine payouts last year...that's up four percent from the year before.The New York Daily News reports nearly 700,000 quality of life fines were handed out...up 51 percent since 2013.They include crimes such as littering and noise pollution...City Comptroller Scott Stringer says the increase is meant to discourage harmful behavior, citing the citywide campaign Vision Zero to reduce traffic deaths.Parking tickets accounted for 55 percent of all fines, bringing a total of $545 million to the city.In contrast, fines against restaurants and small businesses have decreased, in line with a campaign promise by New York Mayor Bill de Blasio to ease financial burdens on city businesses.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.036 |
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".