🔍 Focus: Valid, reliable, and transparent psychometric tools · Algorithmic analysis of social interaction sequences
An open-source personality inventory for transition-class students
📊 Valid · Reliable · Objective · Transparent
Since 2012, the Düsseldorf Student Inventory (DÜSK) has served as an open learning and research platform for:
- Students in the social sciences
- Trainees in market and social research
- Developers and data analysts
Features
- ✅ Full source code (PHP, MySQL, Xamarin, Lazarus, etc.)
- ✅ Open raw data + SPSS/R data files
- ✅ Cross-platform: Web · PC · Android · iOS
- ✅ For research, teaching, and applied practice
📌 Collaboration invited
Joint development and distribution via app stores (Google Play, App Store, Amazon).
Algorithmic Recursive Sequence Analysis for Explainable AI in Qualitative Social Research
ARS_ExplainableAI is a methodological and software-based framework for Algorithmic Recursive Sequence Analysis (ARS).
It integrates qualitative hermeneutics with formal modeling and contributes to Explainable Artificial Intelligence (XAI) in text analysis.
This repository contains:
- Complete scientific papers on ARS methodology (German / English)
- Python implementations for grammar induction from terminal symbol sequences
- Advanced network modeling via transformation into Petri nets and Bayesian networks
- Compressing principles (repetition, recursion, symmetry, hierarchy)
- Optimization algorithms for iterative adjustment of transition probabilities
- Eight transcripts of sales conversations as an empirical basis
Qualitative social research faces a methodological dilemma:
Generative AI systems promise scalability but evade classical validation due to their opacity.
ARS_ExplainableAI addresses this challenge through:
- Transparent model construction – every interpretative step is explicitly documented
- Formalization of qualitative processes – transformation of interpretations into terminal symbol sequences
- Explainable network models – compressive transformation into Petri and Bayesian networks
- Recursive self-application – AI as an epistemic agent reflecting on its own interpretations
ARS_ExplainableAI ist ein methodologisches und softwaretechnisches Framework zur
Algorithmisch Rekursiven Sequenzanalyse (ARS).
Es verbindet qualitative Hermeneutik mit formaler Modellierung und leistet einen Beitrag zur
erklärbaren Künstlichen Intelligenz (XAI) in der Textanalyse.
Dieses Repository enthält:
- Vollständige wissenschaftliche Aufsätze zur ARS-Methodologie (Deutsch / Englisch)
- Python-Implementierungen zur Grammatikinduktion aus Terminalzeichenketten
- Erweiterte Netzmodellierung durch Transformation in Petri-Netze und Bayessche Netze
- Komprimierende Prinzipien (Wiederholung, Rekursion, Symmetrie, Hierarchie)
- Optimierungsalgorithmen zur iterativen Anpassung von Übergangswahrscheinlichkeiten
- Acht Transkripte von Verkaufsgesprächen als empirische Basis
Die qualitative Sozialforschung steht vor einem methodologischen Dilemma:
Generative KI-Systeme versprechen Skalierung, entziehen sich jedoch aufgrund ihrer Opazität der klassischen Validierung.
ARS_ExplainableAI begegnet diesem Problem durch:
- Transparente Modellbildung – jeder Interpretationsschritt wird explizit dokumentiert
- Formalisierung qualitativer Prozesse – Überführung von Lesarten in Terminalzeichenketten
- Erklärbare Netzmodelle – komprimierende Transformation in Petri- und Bayessche Netze
A rule-based method for causal inference using action grammars and graphs.
Sales Dialogue Analysis & Grammar Induction
- Optimized transition probabilities (Python)
- Multi-Agent-System (MAS) integration
- LLM-assisted category generation
Key Notebooks
- Grammar tools (Lisp/Scheme)
- Parser implementations (Pascal)
- Original transcripts and audio (vkg1.mp3)
I provide:
- Source versions (PHP, Xamarin, Android Studio, etc.)
- Manuals and documentation
You handle:
- Distribution via app stores or web servers
- Revenue sharing agreement
Ways to collaborate:
- Improve GUI design
- Write tutorials (YouTube / technical documentation)
- Expand calibration samples
- Port software to new environments (Eclipse, NetBeans, etc.)
💬 Let’s collaborate on transparent, evidence-based psychometrics.
ARS bridges
- Karl Popper’s falsifiability principle
- Ulrich Oevermann’s objective hermeneutics
- Computational rigor (Bayes · Pearl · Chomsky)
“Unlike postmodern hermeneutics, ARS combines Lisp’s recursion, Python’s scalability, and R’s statistics to model social sequences as explainable graphs.”
Click to expand
English: Seeking partners for open-source psychometric tools and ARS development.
Français: Recherche de collaborateurs pour des inventaires de personnalité open-source.
Español: Modelos de gramática accional para análisis de diálogos.
中文: 开源性心理测量工具开发合作。
This trilogy is not for everyone …
- no explosions or chase scenes
- no heroes or villains
- no confirmation of your worldview
A philosophical thought experiment disguised as a technical thriller —
about posthumanism, algorithms, and the future of democracy.
If you expect entertainment, you will be disappointed.
If you expect to think, you will be challenged.
“Every page demands your thinking – not just your excitement.”
The Last Freedom / Die letzte Freiheit
Your brain will not be spared. / Ihr Gehirn wird nicht verschont.
- GitHub: @pkoopongithub
