Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

igeoo/scipra-ai-mcdm-mineral-policy-africa

Domaine:

environment and energy
Créateur:
ige
Hôte:
AI-enhanced MCDM framework for quantifying policy convergence and stake holder alignment in African mineral resource governance # SCIPRA: Stakeholder-Centric Investment–Regulatory Policy Architecture This repository contains the reproducibility package for the manuscript: **Bridging the Investment-Regulatory-Stakeholder Divide: An AI-Enhanced MCDM Framework for Mineral Resource Policy Convergence in Africa** The repository supports transparent replication of the SCIPRA framework, including the mathematical proofs, NLP–SVM pipeline, stakeholder salience scoring, and supplementary figures. --- ## Repository structure ```text SCIPRA_GitHub_Package/ ├── appendices/ # Supplementary materials and reference files ├── code/ # Reproducible Python scripts ├── data/ │ ├── raw/ # Public-source raw data placeholders │ └── processed/ # Processed/derived datasets ├── docs/ # Data access and reproducibility notes ├── figures/ │ ├── svg/ # Camera-ready SVG figures │ └── tiff_placeholder/# Placeholder for journal TIFF exports ├── results/ # Output files generated by scripts ├── CITATION.cff ├── LICENSE ├── README.md └── requirements.txt ``` --- ## Supplementary material map - **Appendix A**: Mathematical proofs and formal derivations for PCI/RPCI boundedness, monotone convergence, and normalisation. - **Appendix B**: NLP–SVM pipeline specification, lexicons, corpus metadata, and open-source data access pathway. - **Appendix C**: Explicit derivation of stakeholder salience attributes: Power (P), Legitimacy (L), and Urgency (U). --- ## Reproducibility workflow 1. Install dependencies: ```bash pip install -r requirements.txt ``` 2. Prepare the public-source corpus using the access pathway described in `docs/DATA_ACCESS.md`. 3. Run the full end-to-end analysis (NLP-SVM + PCI/RPCI): ```bash python code/execute_full_analysis.py ``` 4. Generate the canonical manuscript table values: ```bash python code/generate_tables.py ``` This produces the authoritative numbers for Tables 5 and 7. The manuscript reports the …

Visit

github.com

Similaires

Ethical Horizons -Mapping AI Policy in Africa Ethical Horizons Mapping AI Policy in AfricaAI Ethical Policy in AfricaAi-West-Africa/aiwa-policyAfrica ∙ An AI Policy Framework for Africaamanuu21/Ai-Education-Africa-Policy-Brief-Institutional Policy Implementation and Uganda’s Mineral Resources Management

Ethical Horizons -Mapping AI Policy in Africa Ethical Horizons Mapping AI Policy in Africa

AI Ethical Policy in Africa

Artificial intelligence (AI) is a rapidly growing sector within the African innovation ecosystem. Am

Ai-West-Africa/aiwa-policy

The complete policy framework for AI West Africa (AIWA) — a Gambian-based publishing, cultural class

Africa ∙ An AI Policy Framework for Africa

amanuu21/Ai-Education-Africa-Policy-Brief-

An independent research brief analyzing the potential of Artificial Intelligence to address educatio

Institutional Policy Implementation and Uganda’s Mineral Resources Management

Purpose: This study examines the Mediating effect of Institutional Policy Implementation on Uganda’s