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Record W4404387391 · doi:10.1177/00111287241295679

Calling the Police via 911 Versus a Non-Emergency Number: Variation Among Telephone Reporting Methods and their Implications for Public Safety

2024· article· en· W4404387391 on OpenAlexaff
Rylan Simpson

Bibliographic record

VenueCrime & Delinquency · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsVariation (astronomy)Telephone numberComputer securityPolice departmentComputer scienceMedical emergencyPsychologyInternet privacyCriminologyStatisticsBusinessEngineeringMedicineMathematicsComputer network

Abstract

fetched live from OpenAlex

Much police activity occurs at the request of the public. Most requests from the public are received by the police via telephone. I assessed and compared the characteristics of ~255,000 police calls for service generated via calls to 911 and non-emergency numbers. Dispatched calls for service generated via 911 calls were, on average, higher priority and dispatched faster and to more officers who arrived quicker and spent longer on-scene than dispatched calls for service generated via non-emergency calls. Nonetheless, many emergent events were reported via non-emergency numbers. I highlight the implications of telephone reporting methods for public safety, interrogate the concept of an “emergency” as it applies to policing, and describe the importance of non-emergency call handling for policing operations.

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 imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.072
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.160
GPT teacher head0.484
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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