Motoring offence statistics for Northern Ireland annual report 2019.
Bibliographic record
Abstract
Key Statistics In 2019, there were 47,065 detections for motoring offences in Northern Ireland, a decrease of 6,846 (13%) offences on the 53,911 detections recorded in 2018. Of the 47,065 detections in 2019, over half (58%) resulted in a referral for prosecution and a further one quarter in endorsable fixed penalty notices. The largest offence group recorded was speeding offences with a total of 7,578 detections in 2019 accounting for 16% of all detections for motoring offences.This was a decrease of 9% on the number recorded in 2018. Insurance offences accounted for 7,560 of all these detections in 2019, a decrease of 14% on the number recorded in 2018.There were a further 4,158 detections related to careless driving offences, 488 fewer offences on the number detected in 2018. Drink or drug driving offences has seen an increase of 2% to 3,005 in 2019 when compared with 2018.Motoring offence statistics for Northern Ireland are collated and produced by statisticians seconded to the Police Service of Northern Ireland (PSNI) from the Northern Ireland Statistics and Research Agency (NISRA). PSNI Official Statistics documentation is available on the Official Statistics section of the PSNI website. What's new in this reportThis report now includes a section dedicated to drink drug driving offences, including number of arrests and top 5 alcohol readings.Within the speeding section it now includes the top speed detected by PSNI officers for each speed limit.New thematic maps have been developed to show the detection rate per 10,000 population across a range of offences. Uses of the statisticsUses of the statistics, based on user engagement, information requests and satisfaction survey feedback include policy making and policy monitoring, performance monitoring, and public interest, by a range of users including PSNI, Policing and Community Safety Partnerships (PCSPs), media and academics.More detail can be found in the Motoring Offence User Guide which can be accessed via the motoring offences statistics web page on the PSNI website.PSNI Statistics Branch welcomes any user feedback on the changes, which can be provided via the email address on the cover page. Related statisticsSources of motoring offences data for other domains include An Garda Síochána -Republic of Ireland and England and Wales.Related statistics include Injury road traffic collision statistics and NI Road Safety Partnership statistics. Things you need to know about this release National Statistics StatusNational Statistics status means that our statistics meet the highest standards of trustworthiness, quality and public value, and as producers, it is our responsibility to maintain compliance with these standards.These statistics were designated as National Statistics in March 2020 following a full assessment against the Code of Practice.Coverage This report provides statistics on the number of motoring offences detected by police in Northern Ireland in 2019.It does not include any detections by the NI Road Safety Partnership.Figures relating to such detections through the Partnership can be accessed via the following link -NI RSP.The range of disposals covered includes those offences dealt with by means of a fixed penalty notice (FPN), speed awareness course and referral for prosecution.Statistics Branch developed the functionality to report on prosecution referrals in 2017, at which point the figures were validated and reported back to 2011.Quality concerns due to the introduction of different information systems prevented any further back dating of the figures.This report presents the most recent motoring offence statistics based on figures that were extracted on 13 th March 2020.As of that date, 99.9% of FPNs for 2019 had been processed, while 0.1% remained pending.Referred for prosecution figures from 1 st January 2018 onwards remain provisional and therefore subject to amendment.The information is also available in tabular format in the accompanying spreadsheets on the PSNI website.Background information and details of the offences included in each offence grouping (Section 6) can be found in the Motoring Offence User Guide on the PSNI website.Please note the figures refer to the number of offences and not the number of persons detected as a person can be detected for more than one offence.Table 2: Number of motoring offences by offence group and month
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.064 | 0.074 |
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".