MétaCan
Menu
Back to cohort
Record W3114765797 · doi:10.1080/07418825.2020.1856399

Dangerous Times? A Routine Activities Examination of the Temporal Patterns of Sexual Offenses over Time

2020· article· en· W3114765797 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJustice Quarterly · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPsychologyCriminologySexual assaultMedicineMedical emergencyPoison controlHuman factors and ergonomics

Abstract

fetched live from OpenAlex

Despite environmental criminologists emphasizing the role that both space and time play in the occurrence of crime, there is still only a small literature on the temporal rhythms of criminal behavior, especially those of sexual violence. Drawing from routine activities theory, this research uses circular statistics to investigate the temporal patterns of 2,260 sexual offenses from a Canadian police database at the seasonal-, monthly-, daily-, and hourly-levels, as well as their consistency over time. Findings suggest that there is a distinct temporal pattern when the unit of analysis is at the seasonal-, monthly-, and hourly-levels, but not at the daily-level. Furthermore, these temporal patterns are relatively consistent from year-to-year. These conclusions support the legitimacy of including a temporal element into current geographically-based sexual offender policies and practices. Pragmatically, these findings may also be used to better inform policing and situational crime prevention efforts to reduce the incidence of sexual crimes.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.305
Teacher spread0.271 · 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