How to use the application
Start by entering a case in the Case tab. Then open Institutions to create the organizational hierarchy, including municipal, state, federal, judicial, and independent institutions.
Use Events to record each accusation, defense, decision, or other occurrence, together with its direction, documentary support, and contradictory information. Every event is a collapsible block: you enter only the last institutional level involved and the levels above it are filled in automatically from the organizational tree.
The Analysis tab calculates six exploratory indicators and identifies patterns across institutional branches. Finally, Report produces an English-language summary suitable for further review, with JSON export and import.
The application keeps its data in this browser only. It does not yet provide permanent cloud storage, user authentication, encrypted evidence management, or statistically calibrated misconduct detection.
The full project description below is provided in English. Use the gear (top right) to change theme, language, background image and the To Do / History memo.
CrimeRevealer — Institutional Injustice and Bias Analysis System
1. Project Overview
CrimeRevealer will be a platform for collecting, organizing, and analyzing allegations of injustice, persecution, wrongful accusations, procedural irregularities, and potential institutional misconduct or compromise.
Its objective is to reduce the imbalance of information and power between accused individuals or organizations and the institutions involved, providing independent tools to understand events, identify patterns, and organize evidence for defense.
The system will not depend on official legal authority to produce informational analyses, although its findings will not replace judicial decisions or expert assessments.
Analytical Principles
Premise 1 — Directionality of Errors
Isolated errors can occur in any direction. However, when multiple irregularities exhibit persistent directional alignment, the system will investigate whether this concentration is consistent with chance or suggests a common underlying factor, such as institutional pressure, administrative incentives, conflicts of interest, persecution, or corruption.
Premise 2 — Institutional Proximity
The hypothesis is that coordinated misconduct among institutionally connected agencies may require less communication, influence, and fewer resources than coordination among institutionally distant agencies.
The application will examine this hypothesis using the hierarchical, functional, and territorial structures of the institutions involved.
Premise 3 — Information Quality
Each allegation will be classified according to its origin, supporting documentation, verifiability, source independence, and the existence of contradictory information.
Premise 4 — Pattern Distribution
The application will distinguish between concentrations limited to a single agency, concentrations involving multiple agencies within the same institutional branch, and patterns distributed across different branches of government or independent institutions.
The concentration of errors alone will not establish corruption or coordination. The system will distinguish observed patterns from hypotheses intended to explain them.
2. Multilevel Institutional Structure
Example of an organizational hierarchy with configurable hierarchical codes:
Region / Municipality 1 — Municipal Government 1.2 — Municipal Guard 1.3 — Department of Finance 1.3.2 — Tax Inspection Division 2 — Judiciary 2.1 — Court 2.1.1 — Judicial Division 0 — External / Independent Agencies 0.3 — Consumer Protection 0.3.3 — Consumer Defense Service
These codes are internal identifiers, not official legal classifications. The system will also be capable of representing functional relationships between agencies that do not share the same hierarchical structure.
Each record may indicate whether an institution participated in the accusation, defense, investigation, adjudication, inspection, or oversight process.
3. Proposed Analytical Indices
| Index | Interpretation |
|---|---|
| ICF | Reliability of sources and documents |
| IAD | Directional alignment of events |
| ICI | Institutional concentration |
| IPI | Proximity among involved institutions |
| IEV | Availability of verifiable evidence |
| ICIx | Information independence and contradictions |
Reports must present the calculated values, calculation methodology, limitations, and additional documents that could improve the analysis.
The final classification may identify apparently scattered patterns, concentrations within a single agency, concentrations among closely connected agencies, or alignment across different institutional branches.
4. Application — Version 1
Included features
- Case registration for individuals and legal entities, using either pseudonyms or identifying information.
- Agency registration with variable-depth hierarchical structures.
- Recording of accusations, defenses, decisions, and other events, each as a collapsible block with an instance-level field (enter the last level; the levels above are filled from the tree).
- Classification of source quality and independence.
- Interactive institutional organizational chart.
- Calculation of six exploratory indices.
- Identification of documentary gaps.
- Markdown reports and JSON export / import (drag and drop a file or a folder).
How to run
Extract the ZIP archive and either open index.html in a browser or run python run.py in the application directory. Data is stored locally in the browser.
5. Next Development Stage
To transform the prototype into an institutional investigation platform, the recommendation is to add a trend analysis engine that compares observed events against models of independent errors, dependencies among sources, and hypotheses of institutional influence.
It will also be important to incorporate a network of non-hierarchical relationships — such as information sharing, referrals, functional dependencies, and conflicts of interest — to distinguish administrative proximity from potential coordination.
The delivered version is functional as a local prototype but does not yet include authentication, encryption, document attachments, or calibrated statistical inference. Therefore, it should not be used to process real sensitive personal data until these safeguards have been implemented.
Ultimate objective: to enable an accused individual to identify not only which institutions participated in their case, but also where events are concentrated, which sources are independent, what contradictions exist, and what additional evidence could help clarify the origin of a pattern of institutional conduct.
Case registration
This demonstration stores information in this browser only. Do not enter real sensitive personal data. Use fictional or anonymized examples.
Case saved.Institutions and hierarchy
Build the organizational tree. In each record enter only the parent (the last level above): the levels above it are filled in from the tree.
Institutional organizational chart
Institution records
Events and facts
Each accusation, defense, decision or other fact is a collapsible block. In Instance level type the last institutional level involved (code or name); the levels above are filled in from the tree.
Exploratory analysis
Patterns are observations, not proof of corruption or coordination. Indices are exploratory and are not statistically calibrated; they do not replace judicial decisions or expert assessments.
Method
- ICF — mean over events of source weight × documentary support (official/court 1.0, independent third party 0.7, testimony 0.5, media 0.4, self-reported 0.3; support none 0.1, partial 0.55, full 1.0).
- IAD — |adverse − favorable| / (adverse + favorable); needs at least 3 directional events. A two-sided exact binomial p-value against a 50/50 split is shown as a rough guide only.
- ICI — Herfindahl concentration of events across the institutions entered at the instance level (1.0 = all in one institution).
- IPI — mean over pairs of involved institutions of (depth of the closest common ancestor) / (depth of the deeper institution); 0 means different branches.
- IEV — mean documentary support (none 0.1, partial 0.55, full 1.0).
- ICIx — independence (independent 1, partly 0.5, unknown 0.25, dependent 0) × (1 − share of events flagged as contradicted).
Classification: ≥ 60 % of events in one institution → single-agency concentration; ≥ 60 % within one top-level branch → concentration among connected agencies; directional alignment (IAD ≥ 0.6) across two or more branches → cross-branch alignment; otherwise apparently scattered. Fewer than 3 events → insufficient data.