Measuring Global Consciousness? | Roger Nelson Ph.D.
GCP Effects: Global Consciousness or Goal Orientation? [SSE]
Roger D. Nelson
Global Consciousness Project, Princeton NJ, USA, Email: firstname.lastname@example.org
Cumulative results of an experiment spanning 17 years and 500 events supports the proposal of global consciousness (GC), which can be envisioned as a field-like effect. But there is an alternate interpretation recently advocated by Peter Bancel (2014, 2016), namely that the GCP result is due to a goal-oriented (GO) effect similar to the DAT model of May, et al. (1995), which says precognized feedback from future experimental results can influence choices made in the experiment. Earlier, Bancel (2011) compared these models and concluded: “the GCP data reject the DAT model with moderately high confidence. [And] one can show that a similar procedure which tests the alternate hypothesis of a physical effect accepts that hypothesis as being consistent with the data.”
Bancel’s new perspective assumes the XOR that conditions RNG data would also remove any effect of consciousness because that would require physically changing a bit from 0 to 1 or vice versa. This would demand virtually impos- sible microsecond synchronization of effects and XOR timing. In contrast DAT or GO requires no physical effect, only psi- enhanced decisions for event and analysis parameters that will produce future results aligned with experimenter goals.
We expand the picture to include secondary analyses addressing questions that had not been asked in the experi- mental design, and were not considered in event selection. These show data structure which is incompatible with GO.
1. In addition to the primary correlation of RNG means across the network, there is a substantial second order cor- relation of the variances.
2. On average, it takes about half an hour for the cumulative deviation to peak, followed by an hour or two of steady state and then a decline.
3. Correlation strength decreases as the separation between RNG pairs increases, but only during small, relatively local events.
4. The effect size is a function of time-of-day. It is largest in the local afternoon, and smallest in the middle of the night. It depends on whether we are awake or asleep.
5. Post facto analysis shows the trial data are autocorrelated. This was not a “goal” of the experiment, but it is a natural expectation for a field-like model.
6. There is evidence for true negative outcomes in an estimated 17% of GCP events. This is not compatible with the GO model, being actively contrary to the experimenters’ hypothesis and expectations. (Bancel and Nelson, 2008)
Such indicators of structure fit the GC model naturally, but they require a tremendous stretch for GO. Postulating that everything one finds in the data is only there because of experimenter intention is tantamount to giving up on experimental design, and giving in to unfalsifiability. The data demand more generous models, which accommodate multiple sources of effects.
Recorded at the Society for Scientific Exploration Conference (2016)
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Published on November 22, 2018