Hey, here’s $100,000 down the drain!

· Source: Statistical Modeling, Causal Inference, and Social Science · Field: Science & Research — Mathematics & Computational Sciences, Social Sciences & Behavioral Studies, Research Methodology & Innovation · Depth: Advanced, quick

Summary

Social RV, a platform for collecting and analyzing Remote Viewing sessions, has issued a Request for Proposals (RFP) offering $25,000 to $100,000 in ResearchCoin (RSC) for academic research. The funding aims to advance scientific understanding of Remote Viewing, a protocol for non-local perception developed at Stanford Research Institute. Researchers are invited to validate Social RV's data collection methodologies, analyze a dataset of over 3,000 sessions from more than 400 participants, and design innovative experiments using their technological infrastructure. Specific research tracks include methodology validation (e.g., blockchain verification, AI evaluation), comprehensive statistical analysis of the dataset, and experimental innovation leveraging the platform for new tasking types and data collection methods. The RFP targets statistical, computational, psychological, or methodological approaches.

Key takeaway

For AI Scientists or researchers evaluating funding opportunities, you should critically assess the scientific rigor and potential impact of grants, especially those involving unconventional phenomena or non-fiat currencies like ResearchCoin. Consider the long-term value and convertibility of such funding, and whether the research aligns with established scientific methodologies, before committing resources to projects like validating Remote Viewing.

Key insights

A grant offers up to $100,000 in ResearchCoin for scientific validation of Remote Viewing phenomena.

Principles

Method

The proposed research involves validating data collection, analyzing a 3,000+ session dataset, and designing novel experiments using Social RV's platform infrastructure, including blockchain and AI evaluation systems.

In practice

Topics

Best for: AI Scientist, AI Researcher, Research Scientist, Data Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Statistical Modeling, Causal Inference, and Social Science.