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cff-version: 1.2.0
message: "If you use rmorie in your research, please cite the software (see preferred-citation below). Methodology and empirical-applications papers (MRM framework, criminological Hawkes process, solitary-confinement / self-excitation / institutional churn) are in preparation and will be added once publicly available with DOIs."
title: "rmorie: Multi-domain Open Research and Inferential Estimation in R"
authors:
- family-names: "Ruhela"
given-names: "Vansh Singh"
orcid: "https://orcid.org/0009-0004-1750-3592"
affiliation: "Centre for Criminology and Sociolegal Studies, University of Toronto"
name-particle: "Singh"
# IPA: /ʋənʃ sɪŋ ɾʊˈɦeːlɑː/
version: "1.3.2"
date-released: "2026-09-21"
url: "https://github.com/rootcoder007/rmorie"
repository-code: "https://github.com/rootcoder007/rmorie"
license: "AGPL-3.0-or-later"
keywords:
- "criminology"
- "police-oversight"
- "special-investigations-unit"
- "siu-parser"
- "ontario-siu"
- "police-data-mining"
- "carceral-data"
- "mrm-framework"
- "causal-inference"
- "hawkes-process"
abstract: "rmorie is an R toolkit for causal inference, survey sampling, psychometrics, point-process modeling, and Canadian criminological accountability analysis, hosting the MRM (Multilevel Reconciliation Methodology) framework. It includes the first open-source parser and data-mining subsystem for the Ontario Special Investigations Unit (SIU) director's-report corpus, created by Vansh Singh Ruhela: a fetch/parse/analyse pipeline that extracts a 64-column structured schema from SIU director's reports across all three of the site's historical layout generations and pipes it into causal, spatial, and self-exciting point-process models."
preferred-citation:
type: software
title: "rmorie: Multi-domain Open Research and Inferential Estimation in R"
authors:
- family-names: "Ruhela"
given-names: "Vansh Singh"
orcid: "https://orcid.org/0009-0004-1750-3592"
affiliation: "Centre for Criminology and Sociolegal Studies, University of Toronto"
year: "2026"
url: "https://github.com/rootcoder007/rmorie"
references:
# Methodology + empirical-applications papers are in preparation and
# will be added once publicly available with DOIs or preprint URLs.
- type: software
title: "Claude — Anthropic frontier model family"
authors:
- name: "Anthropic, P.B.C."
year: "2024"
url: "https://www.anthropic.com/claude"
notes: "Frontier AI assistance used during rmorie development. Author retains full responsibility for code and methods."
- type: software
title: "Claude Code — official command-line interface for Claude"
authors:
- name: "Anthropic, P.B.C."
year: "2024"
url: "https://claude.com/claude-code"
notes: "Primary development assistant for the rmorie codebase."
- type: generic
title: "Predictive Policing in the City of Chicago"
authors:
- family-names: "Lachérade"
given-names: "P."
- family-names: "Szabo"
given-names: "B."
- family-names: "Krikava"
given-names: "J."
- family-names: "Aeby"
given-names: "M."
year: "2021"
url: "https://github.com/marquito95/Predictive-policing-Chicago"
notes: "SciencesPo 'Decoding Biases in AI' project auditing Chicago's Strategic Subjects List for racial bias. rmorie's predictive-policing calibration audit (morie_frns_predpol_*) is an independent clean-room reimplementation of this project's published methodology -- no code copied."
- type: article
title: "Unmasking Algorithmic Bias in Predictive Policing: A GAN-Based Simulation Framework with Multi-City Temporal Analysis"
authors:
- family-names: "Barman"
given-names: "Pronob Kumar"
- family-names: "Barman"
given-names: "Pronoy Kumar"
year: "2026"
url: "https://arxiv.org/abs/2603.18987"
notes: "Source of the four temporal bias metrics and the composite Bias Amplification Score reimplemented in rmorie's fairness modules."
- type: generic
title: "XAI Stories: Case Studies -- COMPAS Recidivism"
authors:
- family-names: "Biecek"
given-names: "Przemysław"
- name: "et al."
year: "2021"
url: "https://pbiecek.github.io/xai_stories/story-compas.html"
notes: "The COMPAS explainability audit whose explainer recipe rmorie's fairness XAI module independently reimplements."