The Global Consciousness Project

 
What is the nature of Global Consciousness?

Methodology


This is an old page. For current descriptions, see: The science.




Introduction

The scientific aspects of this project will develop over time, as experience is gained. This page discusses our present understanding of the methods and constraints we believe will yield clear, interpretable results with regard to our basic prediction of a correlation of REG behavior with identifiable states of collective consciousness. The discussion is ongoing, and some alternative proposals are under consideration as complements to the currently planned approach. A recent letter with statistical questions is an example of the value of constructive skepticism. The ability to gather and interpret scientific evidence depends fundamentally on a clear statement of the hypothesis or the question that is being asked. We use operational definitions to ensure that we can extract quantitative conclusions from data, with specific relevance to our questions. We have used more than one defined analysis over the course of the experiment, for which the detailed recipes are provided. If followed, these will duplicate the original GCP analysis. (In some cases, extra data will have been accumulated from dial and drop eggs.)



Primary Hypothesis

The composite variation of the distribution means of data sequences (segments) recorded from multiple REGs during broadly engaging global events will deviate from expectation.

Definitions

The variance measure is the Chisquare-distributed, squared composite of the normalized deviations (Z-scores) of segment means from chance expectation. Formally, Chisq = (Sum(Z)/Sqrt(N))^2.

The distribution means are those of data segments from each continuously-running REG, recorded during the specified time period. The length and hence the number of sub-segments within the period are pre-specified.

The identification of broadly engaging global events is made by the experimenters prior to the event or prior to any examination of the data. The identifications or predictions are based on intuition and experience, and on relatively objective criteria such as intensity and depth of media coverage.