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Record W3122981371

Safety and Security: A proposal for Internationally Comparable Indicators of Violence

2007· preprint· en· W3122981371 on OpenAlexfundno aff
Rachael Diprose

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2007
Typepreprint
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
FundersDepartment for International DevelopmentAustralian Agency for International DevelopmentUniversity of OxfordUnited States Agency for International DevelopmentInternational Development Research CentreGovernment of Canada
KeywordsNexus (standard)PovertyCausality (physics)Interpersonal communicationDomestic violencePolitical scienceCriminologyEconomic growthPsychologyPoison controlSocial psychologyHuman factors and ergonomicsEconomicsMedicineEngineeringEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Violence impedes human freedom to live safely and securely, and can sustain poverty traps in many communities. A key challenge for academics, policy makers and practitioners working broadly in programs aimed at poverty alleviation, including violence prevention, is the lack of reliable and comparable data on the incidence and nature of violence. This paper proposes a household survey module for a multi-dimensional poverty questionnaire which can be used to complement the available data on the incidence of violence against property and the person, as well as perceptions of security and safety. Violence and poverty are inextricably linked, although the direction of causality is contested if not circular. The module uses standardised definitions which are clear, can be translated cross-culturally and clearly disaggregate different types of interpersonal violence, thereby bridging the crime-conflict nexus.

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)0.065
metaresearch head score (Gemma)0.124
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.343

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.124
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0210.025
Science and technology studies0.0020.006
Scholarly communication0.0080.013
Open science0.0060.011
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0090.004

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 head0.087
GPT teacher head0.394
Teacher spread0.308 · 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 designTheoretical or conceptual
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

Citations11
Published2007
Admission routes1
Has abstractyes

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