154
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PROCEEDINGS OF THE IEEE, VOL. 70, NO. 2, FEBRUARY 1982
TABLE III
Precognitive Remote Perception 24 X 24 “Chicago” Series
Proper Target Ranks
Perception No.
Scoring Method 3
Avg.
Avg./24
Human Judges
Mean Rank b
A
B
C
D
E
3/4
5.9
0.25
2.7/8 = 0.34
1/2
1.9
0.08
1.0/8 = 0.13
1.0
0.04
1.5/8 = 0.19
2/8
7/2
2/2
4/2
2/2
4.5
0.19
2.7/8 = 0.34
7/3
8.0
0.33
1.7/8 = 0.21
9/5
12/2
7/2
16/2
7/2
11.0
0.46
3.5/8 = 0.44
13/2
12.3
0.51
2.3/8 = 0.29
20/3
19.2
0.80
1.8/8 = 0.23
4/2
4.5
0.19
2.6/7 = 0.37
10/7
10.6
0.44
1.4/7 = 0.20
9/4
9.7
0.40
3.6/7 = 0.51
1/3
2.6
0.11
1.8/7 =0.26
1/3
2.0
0.08
2.2/7 = 0.31
1.4
0.06
1.4/7 = 0.20
1/2
.
1.5
0.06
1.0/7 = 0.14
1.8
0.08
1.0/10 = 0.10
1/4
4.5
0.19
1.0/5 =0.20
2/2
'
4.1
0.17
1.0/5 = 0.20
14/3
15.8
0.66
unjudged
7/6
9.9
0.41
5.0/6 = 0.83
1/2
2.3
0.10
2.0/6 = 0.33
5/6
7.1
0.30
3.0/6 = 0.50
16/4
15.1
0.63
3.0/6 = 0.50
3.4
0.14
2.0/6 = 0.33
Mean
6.73
7.75
7.13
5.96
5.79
6.67
0.28
0.31
a Computed rank/number of ties for that rank.
bAssigned rank/number of possible ranks.
arbitrary process of descriptor response. A “selective” scoring/
normalization process has also been applied which effectively
allows the percipient to reject any descriptor on which he feels
unqualified to comment, and thence to be scored only on the
reduced descriptor set.
The statistical significances of these various normalized per-
ception
scores
are
assessed by
a
collective
ranking process
reminiscent of the traditional human judging techniques, but
having
the advantages that the ranking proceeds on a much
more standardized and analytical
basis, and that many more
alternative
targets can be ranked by the machine than by a
human judge.
Specifically, the program scores each transcript
not only against its proper target, but against every other tar-
get in the pool, and then ranks these targets in order of descend-
ing score and specifies the rank of the match with the proper
target.
This process
is repeated for every scoring method, and
the results displayed in corresponding matrix arrays.
Table
III displays typical results of these analytical ranking
procedures as applied to a group of 24 perceptions of 24 targets
in the Chicago area.
Tabulated are the ranks of the proper tar-
gets compared with all other targets for each of the perception
efforts,
as computed by five of the scoring methods we have
found to be most instructive, namely. A) number of correct
descriptors/total number of descriptors; B) weighted
full de-
scriptor score/perfect score; C) weighted full descriptor score/
number of descriptors; D) weighted selective descriptor score/
perfect score; and E) weighted selective descriptor score/chance
score.
Also included in the table are the mean ranks assigned by
independent human judges
subjectively comparing these per-
ceptions with a much smaller number of alternative
targets.
Although
the
bases
of comparison
are
quite
different,
it
appears that in the majority of these cases the analytical and
impressionistic
evaluations
concur
at
least roughly
in
their
estimate of the quality of the perceptions, particularly for those
which consistently obtain low rank assignments.
If the analyt-
ical computation
is carried through using as target pool only
those
alternative
targets
available
to
the human judges, the
agreement in mean ranks is found to be somewhat closer, per-
haps fortuitously so, given the categorically different bases of
assessment implicit in the two methods.
To this analytically scored and ranked data it
is possible to
apply
a
variety
of
statistical
assessments
of widely
ranging
sophistication
and
complexity.
Consistent with
the
rather
broad mesh of the descriptor code and the elementary scoring
recipes invoked in this version of the concept, we confine our-
selves
to
correspondingly
simple
statistical measures which
provide at least semi-quantitative indication of the yield beyond
chance.
Specifically, we address only the distribution of proper
target ranks achieved in the series of perceptions, such as sum-
marized in columns 2-6 of Table
III.
Using the common z-
score method
for
a
discrete
distribution, the probability of
achieving the mean rank of any of these columns by chance
may be directly computed.
Table IV displays the results of
such calculation for the same 24 X 24 “Chicago” series. Note
that, whereas all of the methods suggest significant departures
of the computed mean ranks from chance, there is relatively
little disparity among them, indicating that the specific method
of scoring and normalization is not a sensitive element in the
overall evaluation of the perception series.
The departure of the shape of the proper target rank distribu-
tion from chance is also displayed in Table IV in terms of the
number of perceptions achieving first-place ranks, the number
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JAHN: PSYCHIC PHENOMENA: ENGINEERING PERSPECTIVE
TABLE IV
Precognitive Remote Perception 24 X 24 “Chicago” Series
Score Summary
155
Method®
Mean
Rank
No. 1st (2nd)
Ranks
No. Ranks
Below Mean
Z
Pz
,
X 2 (4)
'x
Chance
expectation
12.5
1.0
(1.0)
A
6.73
4.4
(4.0)
-4.08
2 X 10-5
18.5
<0.005
B
7.75
2.0
(6.0)
-3.36
4 X 10"4
11.8
<0.01
C
7.13
2.0
(4.5)
-3.80
7 X 10_s
19.6
<0.001
D
5.96
8.0
(2.0)
-4.63
2 X 10-6
24.0
<0.001
E
5.79
6.0
(3.5)
-4.75
1 X 10-6
27.6
<0.001
aAs described in text:
A) Number of correct descriptors/total number of descriptors.
B) Weighted full descriptor score/perfect score.
C) Weighted full descriptor score/number of descriptors.
D) Weighted selective descriptor score/perfect score.
E) Weighted selective descriptor score/chance score.
TABLE V
Precognitive Remote Perception 6 X 24 “Ocean” Series
Score Summary
Method®
Mean
Rank
No. 1st (2nd)
Ranks
No. Ranks
Below Mean
Z
Pz
Chance
expectation
12.5
0.25
(0.25)
A
4.5
1.0
(1.1)
-2.83
0.002
B
4.2
2.0
(0.0)
-2.95
0.002
C
5.0
1.0
(1.0)
-2.65
0.004
D
5.2
1.0
(0.5)
-2.59
0.005
E
5.3
1.0
(1.0)
-2.54
0.006
aAs described in text:
A) Number of correct descriptors/total number of descriptors.
B) Weighted full descriptor score/perfect score.
C) Weighted full descriptor score/number of descriptors.
D) Weighted selective descriptor score/perfect score.
E) Weighted selective descriptor score/chance score.
ranked better than the chance mean, and a simple X
2 test with
its associated probability.
The method is not restricted to square arrays,
i.e., to equal
numbers of targets and perceptions in one-to-one correspon-
dence.
Table V displays the results of a recent “Ocean” series
in which six perceptions were ranked against 24 targets in the
pool from which the six actual targets were drawn. (The per-
cipient
for
this
series was at the time sailing alone across the
North Atlantic Ocean.)
Because of its particularly severe protocol, we also include as
illustration the results of a “European” series judged by this
method.
In
this
series,
the
agent was
traveling
in
eastern
Europe, and on
five successive days, at 3:00 P.M. local time,
utilized whatever location he happened to occupy as the target.
The perceptions of these
targets were recorded by a single
percipient in northern Wisconsin at approximately 8:30 A.M.
local
time
of the
preceding day,
i.e., each
perception was
roughly 24 h precognitive.
(Fig. 22 depicts a target and percep-
tion from this series.)
Table VI displays the analytically judged
results of this
series, and compares them with the results of
previous human judging.
Although the data base is small, the
consistency of yield is striking.
To obviate the possibility that this method of analysis may
somehow process even random inputs to apparently significant
scores,
artificial target data matrices and artificial perception
data
matrices have been constructed from the output of an
REG, and the computational schemes applied to various com-
binations of these with each other and with true data.
The
pattern
of
results
conforms
to
chance
expectations.
An
alternative form of control
is provided by application of the
method
to
discemibly
unsuccessful
test
series, which yields
appropriately insignificant results.
The project outlined in the last few paragraphs
is described
in
greater
detail,
with many
other experimental examples,
both successful and unsuccessful, in reference
f 1 79]
. We have
since developed
the
capability
of employing ternary
rather
than binary responses to the
descriptors, in order to convey
more shaded information about the aspects queried. A given
feature may thereby be specified as a) present and dominant;
b) present but secondary; or c) absent.
Or alternatively, the
feature may be described as a) definitely present; b) ambiguous
or unspecified; or c) definitely absent.
While these approaches
clearly provide more specific target and perception data, the
scoring thereof becomes more complex, especially in the defini-
tion of certain of the normalization denominators.
We have also been exploring a modification of this analytical
judging procedure which would bypass the ranking steps alto-
gether and move directly to compute individual statistical scores
for each transcript.
The key to this variation is the definition
and utilization of a generalized target pool composed of over
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February 1982
TABLE VI
Precoonitive Remote Perception 5X5 “European” Series
Score Summary
Method®
Mean
Rank
No. 1st (2nd)
Ranks
No. Ranks
Below Mean
z
Pz
Chance
expectation
3.0
1.0
(1.0)
A
1.2
4.3
(0.3)
-2.85
0.002
B
1.4
4.0
(0.0)
-2.53
0.006
C
1.4
3.0
(2.0)
-2.53
0.005
D
1.8
4.0
(0.0)
-1.90
0.029
E
1.6
3.0
(1.0)
-2.21
0.013
Seven human
judges (avg.)
1.9
2.1
(1.6)
4.6
aAs described in text:
A) Number of correct descriptors/total number of descriptors.
B) Weighted full descriptor score/perfect score.
C) Weighted full descriptor score/number of descriptors.
D)
Weighted selective descriptor score/perfect score.
E)
Weighted selective descriptor score/chance score.
200 targets, local, national, and international, assembled for a
broad range of earlier and ongoing experimental series, from
which
correspondingly generalized a priori descriptor proba-
bilities may be calculated.
Evaluation of the transcript scores
on
the
basis
of these
generalized
probabilities,
rather than
those calculated
for the specific series target pools, has been
found to alter only slightly the relative ranks of the perceptions
determined by any of the five methods used above and provides
the desired common basis for evaluating the individual statis-
tical significance of those scores.
To pursue this, the program next assembles a set of empirical
chance distribution functions, one for each scoring method, by
concatenating
all mismatched
perception
scores assigned by
that method,
i.e.,
all off-diagonal elements of that perception-
target matrix.
With reference to Gaussian fits to these empiri-
cal chance
distributions,
the proper perception-target scores
can then be assigned z-values and corresponding probabilities
against “chance.”
As one example of this approach, Fig. 23
shows the empirical
distribution of scores compounded from
some 1400 mismatched
targets and transcripts by method E,
on which are superimposed the scores achieved by the 24 proper
target perceptions of the “Chicago” series. The corresponding
r-values and probabilities against chance are listed in Table VII.
These individual significance values can subsequently be com-
pounded into an overall significance level for the entire series
by various standard procedures [180], The latter result should
agree with that derived from the original ranking method, to
the order of approximation implicit in each form of this anal-
ysis.
In this case, the series value is about 10~8
, compared to
10” 6 for the ranking method.
The specific results shown in Tables III—VII represent some of
the most successful data we have acquired; many less successful
examples could also be displayed. To summarize our total ex-
perience with over two hundred remote perception efforts, all
performed with volunteer percipients claiming no special abili-
ties, we might note that the data tend to
fall into one of four
categories, in roughly comparable quantity:
1)
the target is accurately represented in detail and composi-
tion;
2)
particular features of the target are accurately perceived,
but the context is incorrect;
3) the ambience of the target
is perceived, but the details
are inaccurate;
Fig. 23.
Remote perception empirical chance distribution (method E).
4)
the perception seems unrelated to the target in context
or detail.
Survey of the pertinent literature indicates a comparable pat-
tern of yield across the experience of others involved in similar
experiments.
To date there has been little progress in correlating the degree
of success
of such
efforts
with the
prevailing experimental
conditions
or with the personality
traits or attitudes of the
participants. A certain body of lore has compounded from the
testimony of the more successful percipients, such as the desir-
ability of a personal rapport between the agent and percipient,
the value of a lighthearted attitude, the importance of exclud-
ing any associative or constructive logic, etc., but much of this
is
still too vague and inconsistent to provide any basis for ex-
perimental refinement
or
theoretical modeling.
At present,
the only
fair statement would be that empirical evidence for
this
class of phenomena
continues to accumulate, but with
frustrating
irregularity and
little basic comprehension.
Not-
withstanding,
the
present and
potential
applications
of the
process
in
a variety of arenas, combined with the relatively
simple and inexpensive
nature of the experiment, keep
this
type of study active.
Theoretical Concepts
No remotely satisfactory physical theory of psychic phenom-
ena yet
exists.
Indeed, next to the evasiveness of the effects
under controlled experimentation, the second greatest frustra-
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*
1982
&
I
sthod E).
context
able pat-
n similar
lie degree
irimental
is of the
from the
the desir-
srcipient,
if exclud-
ch of this
iis for ex-
I present,
dence for
but with
on.
Not-
ts
of the
relatively
keep
this
d phenom-
he effects
tst frustra-
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JaHN: PSYCHIC PHENOMENA: ENGINEERING PERSPECTIVE
TABLE VII
Precognitjve Remote Perception Individual Statistical Scores
(Method E) 24 X 24 “Chicago” Series
Perception No.
z-score
Pz
1.210
0.113
0.089
0.465
2.737
0.003
1.700
0.045
-0.553
0.709
1.533
0.063
-0.315
0.623
-0.315
0.623
0.451
0.326
-0.197
0.578
0.191
0.424
2.037
0.021
2.948
0.002
2.244
0.012
2.661
0.004
2.478
0.007
2.180
0.017
1.904
0.028
0.083
0.467
-0.152
0.560
2.679
0.004
0.701
0.241
1.057
0.145
0.113
0.455
tion in the study of psychic processes has been the absence of
viable theoretical models with which to begin the traditional
dialogue between theory and experiment on which all scientific
progress eventually depends.
This may, of course, be indicative
of an illegitimacy of the phenomena themselves, or at least of
an
evanescence
that
fundamentally precludes any analytical
representation.
On the other hand,
it may be an indication
that modem physical theory, elaborate and sophisticated as it
is, has not yet evolved to a stage where it can properly acknowl-
edge and deal with the role of consciousness in the physical
world [1811, and that this should be one of its new frontiers.
Before pouncing toward either extreme, it may be worthwhile
to play through some of the more canonical attempts that have
been made to deal with this domain, both from a formalistic
and philosophical point of view.
Efforts toward theoretical explication of psychic phenomena
over the past century have proceeded from various levels of
presumption as to the fundamentality of the effects observed.
Some have insisted that the effects are totally illusory, i.e., arti-
facts of poor experimentation or data processing, or that they
are the chance results of random processes. Others have assigned
the effects to known physical and physiological mechanisms
associated with, but not deliberately precipitated by the partic-
ipants,
e.g., electromagnetic radiation from brain circuitry or
intercardial potentials, or heat transfer, vibration, or aerochem-
ical changes in the experimental environment caused by human
presence or exertion.
More ambitious efforts have contended
that no such conservative models can suffice, and that it will
be necessary to identify new forms of energy or information
transfer to retain the established physical formalisms, or pos-
sibly even necessary to expand the physical laws themselves,
as was required in the generalization from classical mechanics
to quantum mechanics or to special and general relativity, with
the
present forms becoming subsumed under more compre-
hensive statements.
Still others have concluded that the scien-
tific paradigm in general is inadequate and that basic revision
in the representation of the process of conscious observation
of physical events will be required.
Beyond
the uncertainty
as
to the fundamentality of the
model required, these modeling efforts have labored under the
confusion of whether the purported phenomena are most basi-
cally psychological, physiological, physical, or some inextricable
combination thereof, and hence which class of concepts should
dominate the model and which should be secondary.
Virtually
all permutations have been explored to some degree, under
labels
of
“psycho-physiological,”
“biophysical,”
“psycho-
physical,” etc., but none of these can claim more than sugges-
tive
analogies
or
philosophical
stimulation.
This author
is
unqualified
to
assess any models based in the psychological
or physiological domains, other than to note that those most
frequently discussed tend to acknowledge the role of random
processes,
information
ordering, and
statistical,
rather than
directly
causal mechanisms [182] -[187],
all of which have
their counterparts in several of the more physically oriented
modes which have been proposed.
Confining ourselves to such
physical theories, the history of credible analytic effort is con-
veniently short and, in my view, more instructive in its philo-
sophical than in its functional characteristics.
Electromagnetic and Geophysical Models
For perhaps naive reasons, the earliest physical models tended
to presume wavelike propagation of psychic effects, usually in
the electromagnetic modes [188].
Doubtless the concurrent
emergence of radio technology with its revolutionary wireless
capabilities influenced the concepts and nomenclature of these
versions,
and
frequent reference
to psychic
“transmitters,”
“receivers,” “antennas,” “tuning,” and
“static” are found in
them.
Upton Sinclair’s book, Mental Radio, mentioned earlier,
is one example of such an analogy [152].
More modem models of this genre, appearing predominantly
In the Russian literature [43]
, [50], [100]
, [189]
, [190] .have
focused on very low frequency bands, of the order of 10 Hz,
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