Alta 2016 April WEBBOT CLIFF HIGH

8/17/2019 Alta 2016 April WEBBOT CLIFF HIGH

1/32

Asymmetric

LinguisticTrends

Analysis

by clif high

for Halfpasthuman.comcopyright 2016 all rights reserved, claims for invention and labor

Class VI !escueimpossible "

#ay, 2016covering 2016 $ 20%&'age 1 of (2

) 2016 by clif high for Halfpasthuman

Class VI !escue Impossible " #ay, 2016

*ll rights reserved


2/32

Introduction

'redictive +inguistics is the process of using computer softare to aggregate vast amounts of ritten

te-t from the internet by categories delineated by emotional content of the ords. 'redictive+inguistics uses emotional ualifiers and uantifiers, e-pressed as numeric values, for each and all

ords/phrases discovered/filtered in the aggregation process. ver 0 of all the ords gathered ill be discarded for one or more reasons.

'redictive +inguistics or3s as 4 conscious e-pressions are processed through the softare.

!ather the conte-ts discussed ithin the report in the form of entities and linguistic structures 5see

belo are read up in the various inta3e softare programs, and the emotional sums of the language

found at that time are retrieved. 7ords that are identified ithin my system as 8descriptors8 are passed

through the processing as ell. 9hese descriptor ords, in the main, are those ords and phrases that provide us ith the detail sets ithin the larger conte-t sets.

*s an e-ample, the ord 8prophecy8 may be read up by our softare at a sports oriented forum. In that

case, perhaps, due to the emotional sums around the conte-t, and the emotional values of the ord

itself ithin the le-icon, it ould be put into the conte-tual 8bin8 ithin the database as a 8detail ord8. 4ote that the conte-t of the use of the ord in the sports forum is lost in the process and is of no use to

us in these circumstances. 7hat occurs is that the ord is pic3ed up as being atypical in its conte-t,

therefore of high potential 8lea3age of future8 value. 9he ay this or3s is that most sports forumlanguage about future events ould be statistically more li3ely to use ords such as 8bet8 as in 8I bet this

::: ill be outcome8, or 8I predict8, or 8I thin3 that ::: ill happen8. ;o it is the conte-t plus

emotional values plus rarity of use ithin the conte-t that flags ords for inclusion in the detail level of the data base.


3/32

9he ALTA report is an interpretation of the asymmetric trends that are occurring even this instant as

millions of humans are typing billions of ords on the internet. 9he trends are provided in the form of a

discussion of the larger collections of data 5dubbed entities don to the smallest aspect/attribute sept

up from daily discussions ithin that conte-t. 7ithin the *+9* report format, detail ords are provided as noted belo. 'hrases and idiomatic e-pressions are also provided as details. In the main,

geographic references are merely summed, and if deemed pertinent, the largest bag in the collection is

discussed as a 8probable8, or 8possible8 location to the events being referenced ithin the details.In our discussions, the interpretation is provided in a nested, set theory 5fu@@y logic pattern.

Definitions:

Aspects/Attributes are collections of data that are ithin our broader linguistic

structures and are the 8supporting8 sets that provide our insight into future developments.

9he *spect/*ttribute sets can be considered as the 8brought along8 serendipitous futureforecasts by ay of lin3s beteen ords in these sets and the le-icon.

Entities are the 8master sets8 at the 8top8 of our nested linguistic structures and contain

all reference that center around the very broad labels that identify the entity #ar3ets,

Alobal'op, and ;paceAoat


4/32

and also contain emotional quantifiers hich are assigned numeric

representations of the degree of each of the 8cells8 level of 8emotional assignment8.

Spyders are ;oftare programs, that once e-ecuted are self directing, ithin programmed limits, thus are called 8bots8, and ithin these constraints are alloed to

ma3e choices as to linguistic trails to e-plore on the internet. 9he >ob of the spyders is to

search, retrieve and pre$process 5part of the e-clusions process that ill see ?0 of all

returned data eliminated from consideration in our model the 8linguistic bytes8 520%

ords/phrases in multibyte character format hich are aggregated into our modelspace

hen processing is complete.

List of entities e-plored in this report

GlobalPop9he Alobal'op entity represents the linguistic sets ithin the data that are focused on the

future of humanity, local or global. 9he 8local future8 focus language is aggregated into

our 8global future language8 sets. 9his entity is independent of language, alphabet, or

script form, and thus is our deepest and broadest set for emotional uantifiers and

ualifiers about humanity8s future.

USAPop 5and any other nation state/territorial reference

*ll sub sets of the populace of the planet, ithin our modelspace are identified by either

a geospatial term such as a regional terrestrial label, e.g. 8AlpinePop8, or a geopoliticallabel, e.g. 8CanadaPop8. 9hese are used to isolate the subset of the global populace to

hich the terms are being applied in the forecast. 9he terrestrial references are

freuently used to provide a conte-t of 8shared vies/concerns8, as in 8those things all

mountain delling people ill have in common separate from other humans8.

Markets

9he #ar3ets entity is a super set of linguistic structures covering paper debt mar3ets of

all 3inds, commodity trading mar3ets, physical sap mar3ets, currency usage 5ithin

populace, digital currency developments, ne technology 5


5/32

physical environment of planet earth. 9his master set freuently and increasingly has

e-tensive cross lin3s to the ;paceAoat


6/32

Modelspace " in the interpretation, the data sets are represented on screen in a 8virtual bo-8 fashion in

hich a (d bo- is dran and the le-icon lin3ed ords from the latest data processing are shon ithin

the (d bo- by position, and color, brightness and hue of the individual pi-els. Esing an algorithm of myon design and the predicate calculus of the prolog programming language, modelspace is populated

by these data base representations in a manner that resembles 8scatter graphs8, but at a ( dimensional

level. =y toggling on or off several advanced features of our (d bo- softare, the various levels ofdata, and cross lin3s and other technical elements may be displayed.

M$M " model of modelspace. In the very first public release of information from my process, a self$referencing loop as created by internet articles about the release, and thus the ne-t time the spyders

ere invo3ed, the process crashed on self$referential, circuitous references to my on or3. *s a

corrective measure, ## 5models of modelspace as devised as my very improvement on the process. ## holds a copy of my interpretation as ell as lin3s to areas on the net to e-clude from

consideration ithin the predictive linguistic or3.

Set # ur approach involves the use of comple- 5fu@@y set theory originating in the softare industry8suest for 8intelligent machines8 or 8ai 5artificial intelligence8. In our approach, the fu@@y sets are based

on the ability to define such concepts as 8near8, 8close to8, 8about8, and 8li3e8 among many others hich

provide me the ability to assign a numeric representation as a 8uantifier8 to human emotions hich arethe 3ey element to future forecasting from predictive linguistics.

Temporal %co " these are linguistic echos across time that ill reference the same, previouslyforecast, meme and its emotional parameters. 9he language manifest in both instances, that is, the

temporal 5meme anchor and its echo ill be related to each other, though freuently the repeating echo

is larger in both scope and intensity. In some cases the meme is 8completed8 in our predictive linguistics

sense of that ord by the echo phase of the meme.

TM = Temporal Marker, thin3 of this as a 8boo3 mar38 against hich you may remember specific

details of the forecast. 9hese are chosen due to some 5more or less easily identified linguistic 8tell$tale8that e e-pect to sho up in the forecast language ithin media discussions.

'age 6 of (2



*ll rights reserved


7/32

Data and Interpretation

Meta Artsver the years certain patterns have emerged from ithin our or3 that e have formed into postulates

of behavior about the nature of the future lea3s that e harvest here for fun and amusement.

ne of the earlier postulates as that 8the more impacting an event, emotionally and/or temporally, the

further out 5ahead of the event ould the lea3s occur8. It is this 8emotional pressure8 factor that drives

future lea3s 5in my considered opinion ahead of the events.

9here are differing patterns in ho the lea3s accumulate, and their 8breadth versus depth8 groth that

no, some decades into the effort, allo for a bit better vie of the process of the future lea3ing out ofhumans into the ever present no.

In the instance of the 8pressure8 component, e have observed several types over the decades, and

categori@ed them to some small e-tent. *gain, it is the e-perience of participating in the process thatallos the tuning of the process as long as one is aare of one8s on participation8s impact on the

process....hich ma3es sense but hurts to thin3 upon.

9he 8pressure8 component is once again pushing its ay into the general consciousness. ority of humans on the planet emotionally. If it erea sudden event, it may have very high 8pressure8 value as it ould have high emotional intensity, butmay also, not have any 8duration8 value in a meaningful ay.

Terra

9he data continues to gro in support of the 8super hot summer8 sets that have been accumulating ne

sub sets for the 8sharp turn8 from 8rain storms8 to 8dry spells8 and 8intense heat8. et, as repeatedly

mentioned here in the *+9* reports, the global human e-perience is about to be heading into an ice

age, and the 8last of the 5years of oscillations 5beteen heat and cold8 are no fading don to 8only afe8 still ahead of us.

*s may be e-pected the data is uite sure that as the 8pivot8 or 8turn8 into 8more ice age phenomena8 that

'age J of (2



*ll rights reserved


8/32

the last 8heat spells8 ill be the 8most intense e-perienced 5in documented human history8.

9he data sets are describing a 8ilding year8 that ill begin or has already begun and is being described

as actually carrying on for 8several years8. 9he 8ilding8 aspect set includes descriptors for 8out ofseason8 and 8out of place8 attributes for both 8eather8 and 8earth related events8. ;ome of the details

suggest that 8ice bergs8 ill be 8in odd places8 and in 8odd numbers8.


9/32

as ell as 8don hallays8 and 8stairs8. * great many in>uries are shoing as resulting. 9hese sets are

also in direct supporting chain for the previously mentioned Ked note *+9* #archL situation herein

8ships8 had 8too much damage8 and 8too many casualties8 for 8individual rescue 5to be meaningful8.

9he 8oceans8 data set are shoing that 8earth e-pansion effects8 ill be 8evident8 as 8ferry terminal8 ill

8no longer 5uite reach8 the 8boats8 as there ill be 8visible shifts8 in the 8local terrain8. #any of the 8local

>urisdictions8 ill put these effects don to 8local currents8 or 8sedimentation8 or even 8continental drift8.9he forecast is that over the ne-t fe years such 8local currents8 effects ill be popping up very

freuently.

ther 8blame8 is forecast for 8local currents8 in both 8eather8 and climate8, as ell as 8earth changes8.

Ene-pectedly the data is providing 8local currents8 as a 8blame sponge8 for such effects as 8cliffs

crumbling 5into the ocean8, and 8harbors 5filling up ith sedimentation une-pectedly8, as ell as8estuaries broadening out8, and 8reaching bac3 5up river8 as 8ocean shelf surfaces change8. #any of the

grosser effects are forecast as becoming 8visible8 in the 8plethora 5and groing8 of 8stories8 about 8earth

or eather or climate abnormal behavior8.

In some of the data set there are 8ne bar 5conditions8 hich ill form ithin 8tidal river basins8 such

that 8ne ave patterns8 ill manifest that in their turn ill cause 8ide spread regional changes8 to the

local 8ecosystems8 as everything about the local aters changes 8from the bottom up8.

#uch of the 8underseas 5ocean floor changes8 supporting sub sets have cross lin3s over to, or are

directly held by sets ithin the Alobal'op entity for 8food production8. #any of these sets are indicatingthat the 8off shore8 and 8under ocean changes8 ill be the 8direct cause8 for the 8alteration8 of 8nearby

eather patterns8. #ost notably, such an effect is being forecast as impacting 8to 5separated by half the

planet ine groing regions8. In one, 8not enough rain8, and the other 8too much ater8. 9he 8eather

changes8 as a result of the 8deformation 5change8 of the 8sub seas surfaces8 is indicated to 8affect ideregions8 that ill 8e-tend thousand 5or more miles inland8 as the 8ne eather patterns8 ill 8emerge 5in

20168.

9here have been longer term data sets for the formation of 8ne inland seas8 in both 4orth *merica, and

8eastern !ussia 5;iberia8 for a number of years. 9he very first instances began a set that has had

continuing groth, albeit sloly, ever since. 9hese long lived sets have a pattern of escalating shorterterm and immediacy data sets groth before the manifestation of the set meme. 7e have the

beginnings of such a turn no as recent processing has brought in shorter term sets in a meaningful

ay to this linguistic structure for the first time. 9hese ne sets are the first to contain near termreferences and contain data forecasting that 8rivers8 ill become 8dammed8 by 8debris8, both 8man made8

and 8natural8 such that 8ne la3es8 ill be 8reported8 ithin the ne-t fe months. In the case of


10/32

flooding8 in the 8greater ;F 4orth *merica8 over as far as the 8#ississippi !iver valley8. 9hese sets are

suggesting that very 8e-ceptional eather patterns8 ill be 8craling8 over 8north *merica8 in 8counter

cyclical8 motion leaving 8ide spread flooding8 in very 8atypical8 times this year. 9hese 8atypical8 and

8shredding storms 5lots of lightning, inds, and torrential rains, brief, violent8 ill be a 83ey feature8 inthe 8bac3ground8 of the 8presidential theater8 in 2016.

#any of the ne sub sets ithin the 9erra entity are also supporting either directly or via cross lin3s,the 8diaspora8 sub sets for the Alobal'op entity. 9here are a number of ne sets for both entities that are

focusing on the 8diaspora8 of these ne-t 810/ten years8 or so. 9he data sets in the 9erra entity are

presenting this information from the planetary changes point of vie, hile the Alobal'op entity shosit from the viepoint of impacts on humanity.

7ithin the ne forecasts for 2016 arising from the 9erra entity e have the 8oceans 5heaving up precipitation8 sub set in hich the previously forecast, and no confirmed 8ne types 5and intensities

of EV light8 ill be once again the 8precipitating factor 5pun intended8 for 8vast amounts8 of 8ater8

rising from the 8oceans8 and 8heading inland8. 9hese sets are shoing that the 'acific, *tlantic, and

Indian ceans ill be 8evaporating8 at rates that ill be 8visible8 to those 8sailing on them8 as 8day timefogs8 ill be 8seen to lift from mid ocean8.

ther aspect/attribute sets have the 8oceans8 being so 8imbalanced8 that 8vast areas 5the si@e ofcontinents8 ill be 8covered ith floating carcasses8. 9he data sets are describing a time of great

challenge emerging here on earth that ill, as the data sets are shoing, become 8evident8 over the

course of 2016.

9o those humans not totally absorbed in the daily drama of the 8death of the global financial system8,

the 8planetary health8 itself ill be 8demanding8 their attention. 9he data sets are arning of 8e-ceptional

forest fires8 across much of the northern hemisphere including both Canada and !ussia/;iberia. In thecase of ;iberia, the data sets are suggesting that 8geothermal8 causes for many of the 8fires8 ill result

from 8crac3ing8 as the 8planet e-pands8 its 8largest land mass8.

ther problems directly attributable to the 8planetary e-pansion8 are shoing as coming hen a 8large

island8 that is 8inhabited8 ill 8shift8 a bit more 8aay from 5the local mainland8. 9here are a great many

candidates for this 8large island8 including 84e Nealand8, O=ritain8, 8;icily8, O;ri +an3aP and O9aianPto name but a fe. 9he data sets are clearly indicating that 8damage8 on a 8massive scale8 ill result,

though happily, there are many sets for the idea of 8fe fatalities8. 9he data sets are shoing that 8aid8

from 8ships8 ill be 8reuired for months8 to allo for 8habitation to continue8 due to the 8level ofdamage8 involved. 9hese latter sets are arguing for the event to hit an 8island8 smaller than say =ritain,

as that ould reuire global levels of aid and such is not indicated, though the 8aid8 descriptors do sho

a 8long stint8 in the 8recovery process8.

9he 9erra entity, already the largest entity in modelspace, continues to gro ith ne sets indicating a

very large >ump in human focus being put on the planet. 9his is indicated to occur as a result of the

8many ne 5manifesting signs of planetary e-pansion8. 9hese ne signs are shoing as including the previously forecast 5and no appearing 8ne lands8. 9hese 8ne lands8 sets are gaining supporting

'age 10 of (2



*ll rights reserved


11/32

values for 8large eruptions8, and 8very large uplifting8. 9his latter set has a very 8si@able8 chun3 of 8ocean

floor8 that ill 8rise up8 to become a 8ne continent8. *s may be e-pected, this ill cause a hole lot of

language and 8problems8 as the 8ocean currents change8, and 8ne eather patterns begin8. 9hese sets are

shoing that 8populations8 of 8ocean life8 ill be 8affected8 as the 8ne environment forms8. 9hese setsare also suggesting that our previously forecast 8land rush8 language ill start appearing as the 8ne

continent8 is being 8discussed8.

9here continues to be groth in the sets for 8e-cessive heat8 in the northern hemisphere over ;ummer

and ust that 8aves of heat8,

each one described as 8standing8 for a hile, then 8dissipating8 ith mere 8hours8 before the 8ne-t heatave8 forms up. 9hese 8aves8 of 8sun induced heat8 are further described as being 8surface heating8 that

then 8radiates8 out at 8night8 such that many areas ill not even have 8night time cooling8.


12/32

*t the base of all of the many layers of cross lin3s from the 8upheaval8 language, e find repeated cross

lin3s over to the 8fiat currencies race to destruction8, and to 8social instability 5from hyperinflation8.

*s modelspace is moved from late Quly through ;ummer 5northern hemisphere, ne accretion patterns

bring in aspect/attribute sets for 8global depression8, and 8financial system failure8, and 8sovereign ban3ruptcies8, and 8asset 5class failures 5collapse/implosion/deflation8.


13/32

and 8running street battles 5parisM8. *ll of these and many more sets are going to the idea of a very

8tense8 and 8violent8 ;ummer in the Furo@one as both the 8social structure8 and the 8monetary system8

degrade into 8failure8.

9he data accretion patterns for Furo'op have added several ne sets since our last processing. In someof these sets e see that 8armed confrontations8 are forecast for several counties in 8middle europe8 as a

8robbery8 by 8migrants8 goes 8ary8 leading to a 8gang style confrontation8 ith 8police8 that is described

as 8escalating8 to the point of 8shoot outs8.

ther ma>or ne sets for Furo'op include large areas for 8collapsing 5social contract8 as the 8economy8and 8agreements to cooperate8 are 8shattered8 as the 8FE! degrades 5to small fraction of its purchasing

poer8. 9he data sets are bringing in 8ban3 failures8, and 8cross border 5runs on ban3s8. 9hese last sets

are filling ith supporting values for 8ma>or crod problems8 as 8tens of thousands8 of people 8react to

rumors 5of open ban3s/*9#8.

Rata continues to accrue for the 8Italian =an3 crisis8 to 8overhelm8 the 8FE structures8 at several

different levels such that the first 8crac3s8 appear in the 8union8, and 8Italy8, folloed by both Areece and

'ortugal, ma3es moves to 8separate8 from =russels.


14/32


15/32

committee ith a 8too long name8 and it ill then is described as 8percolating up8 through the 8channels8

until it becomes 8officially adopted policy8, and then, seemingly, to the estern orld, ithout any

arning or notice, 8China goes to ;pace8.

9he 8China goes to ;pace 5in a huge, Chinese ay8 is indicated to 8upset8 the 8balance of space poer8,and the 8concepts8 that ere 5til that time 8held 5in the estern military academia8 about 8future

directions 5of China'op8.

USAPop

+anguage about 8aa3ening8 is surfacing throughout the E;*'op entity. #uch of this is referencing the

8reality 5of controlled politics8 here in E;*, but a surprising amount of the ne data goes to the idea of an 8aa3ening8 as to the 8dying credit mar3et5s8 in the 8economy8 of the E;*. 9he data is forecasting

that the 8student debt aa3ening8 is going to hit this ;ummer 5northern hemisphere. 9he data is

indicating that a 8digital problem8 develops in the 8governmental systems8 such that 8payments 5to

homMM8 are 8lost8, and 8ithheld8.

*s a result of the 8impact 5of student debt8 on the 8governmental systems8 5or the reverse, the 8creditsystem8 at the 8retail level8 ithin the E;*'op is forecast to have 8the first spasm8. 9his 8spasm8 isindicated to 8sha3e ban3s8, and 8close auto dealers8, as ell as cause 8sei@ures8 and 8firings8 at

8universities8.


16/32

is destruction at the beginning of all groth phases. ;ame no, and the data is predictive of a level of

8destruction8 that is being described as 8deep into 5the social order8 and 8across all levels as broad as the

nation8. 9he data sets details sho huge crods rioting in ma>or cities as the 8regional problems8

escalate along ith the degrading 8credit/finance system8. 9he 8rioting8 is indicated to be 8sporadic8 andto start later in a 8very hot summer8.

9here are some sets that ould seem to be indicating that a 8political rally 5perhaps even a convention8ill 8spar3 off 5a dispute8 hich then escalates into 8rioting8 several days later. 9hese 8riots8 are also

ithin aspect/attribute sets hich are in the direct supporting linguistic chain for both 8revolution8, and

8international horror8. 9he 8riots8 themselves have many supporting sets that directly cross lin3 over tothe #ar3ets entity here the terminating sets include 8derivative failures 5via insurance or re$insurance

corps8 that then 8flo outard8 into 8sovereign bonds8.

9he data sets are shoing that the E;* 8housing mar3ets8 are going to go through one of the strangest

periods ever. In these ne sets, heavily cross lin3ed over to the #ar3ets entity and the 9'9= entity, e

have ne sets shoing that 8liuidity crisis8 is going to affect so many so abruptly, that 8lu-ury

properties8 ill be 8abandoned8 and 8al3ed aay from8 in numbers never before seen. ;ee #ar3etsentity for more on this from that perspective.

9he E;*'op is holding the vie that the 8high end real estate crisis8 in E;* is a 8stepping stone8 into

8cultural shoc38 and 8change8 as 8mar3ets roll over8. 9his is going to cause a situation of 8rippling effects8as 8real estate active corporations8 lay off their employees. obs being shed hen 8building onership8

instantly becomes a 8liability8 for the 8titular corporation oners8. =asically the idea is that the8companies8 that 8on rentals8 are not in the business for the 8monthly income8 as that does not half cover

real costs, and that hen the 8opportunity8 as ell as the 8future potential8 to 8sell8 is 8removed8 due to the

8spreading credit crisis8, these 8corporations8 ill first try to 8secure government funding8, but ith the

8political chaos8 that uic3ly 8dies8, and then they basically start 8shutting don8, and in the process,8abandoning8 both 8employees8 and 8properties8.

*s may be e-pected, the developing chaos in the real estate mar3ets 5really the 8federally onedmortgage mar3et, cause a no end of 8horrific problems8 for the 8local8 and 8state authorities8. In some

areas the data suggests that 8ta-es8 due to the 8sale8 or 8transfer8 of 8real estate8 are going to 8plummet8

more than 8half8 in >ust a 8fe ee3s8.

9he 8financial chaos8 period indicated by the data sets to occupy much of humanity over 2016 is

described in the data as having a 8bubble8 of 8intensity8 that then is 8slightly8 relieved, before there comesa 8selling 5continuing/groing/encapsulating8 number of years of 8economic pain8 from the 8financial

mismanagement8 and 8overhaul8. 9his 8financial chaos8 period is shoing ithin the movements of

modelspace as e-tending through into the mid 2020s. 9he 8intensity bubble8 is indicated to begin in

#ay and last through to the end of *ugust. 4ote that this 8intensity bubble8 is not shoing as poppingso much as 8e-haling 5once the intensity reaches a pea3 >ust prior to mid Quly8 in 8agony8.

9he individual sub sets providing descriptors for the 8chaos8 are describing a situation ithin E;*'opthat ill be both 8ildly divergent8, and 8idely spread8, as ell as 8don to the toes8. K'lease note body

'age 16 of (2



*ll rights reserved


17/32


18/32

elites8, and 8higher level functionaries8 ill also be among the 8e-cluded8, and thus ill discover that

they are, as ith the rest of us, 8too common8 to be 8alloed in8. 9his is shoing as being a very 8stic3y

point8 for some of the 8near elites8 a 8crushing 5ego blo8 such that they 8ta3e it personally8. ;everal are

indicated to 8respond by gossip 5true info, but of a spiteful nature8 and 8innuendo8 and 8facts8. 9his phaseof the 8social order transformation8 is indicated to be relatively brief as several of the 8spite spea3ing

tongues8 are indicated to be 8severed at the root8. 9he data sets have detail layers indicating that 8>udges8

and 8lobbyists8 and even 8ban3 managers/functionaries8 ill be 8denied entrance8 at the 8door8. 9hese setshave high visibility and broad impact values so e are li3ely loo3ing at a ide meme that ill be

presenting a number of videos during the first fe ee3s of the 8


19/32

emergency meetings8 all the ay up the 8chain of funding/command8. In the data sets are ironic

descriptions of 8state government officialdom8 ho ill be 8in meetings in secret locations8 here they

ill be 8deciding the fates 5of thousands of state and local employees8. 9hese 8functionaries8 then 8arrive

bac3 at headuarters8 only to discover that a 8similar meeting8 had been ta3ing place at a 8higher level8and their hole 8department8 had been 8eliminated hile they ere busily 8eliminating 5someone else8.

;ituations such as these are shoing as one of the many reasons for a 8government structure8 ith 8big

holes8 and 8isolated areas 5that survive " many of hich ill do so simply cause the people going to firethem got fired before they could get around to it8.

ther areas ithin the 8governmental functions caught in funding disarray8 include ne language for8closure of public access points 5par3s, fishing, et al8 ith 8other than funding e-cuses8. 9here are also

sub sets for 8military actions8 in 8ilderness regions8 hich ill cause 8fires8, and 8destroy property8

leading to a 8big cover up8 hich ill 8fail uic3ly8 and then lead to 8investigations8 and 8media [email protected] that occurs, the data sets are suggesting to 8loo3 at hat is not being covered/referenced8 as the

8secret military actions gone bad in nature preserve8 ill be theater designed to 8distract8 and 8dis$

inform8.

* recurring meme groing in the data in a number of diverse sets ithin the E;*'op clusters around

the idea of 8regional energy crises8. 9he data sets are suggesting that a spread of causes ill create

conditions for 8spreading energy crisis8 and 8leaping 5across the grid energy delivery crisis8 as E;*'opgoes into ;ummer. #uch of this language is focusing on a 8splintering 5of usage 5motivations8 here

the 8est8 needs 8heat relief8, ith the east needing 8heat8, and 8eather chaos

5rain/sleet/hail/sno/inds8 are causing problems for the south east. 9he data sets are forecasting that8regional energy crises8 ill morph into 8national food delivery crises8 over much of the rest of 2016 and

201J.


20/32

government pension plan failures8 all of hich are in supporting positions to the 8crashing social order8.

9hese 8pension plan crashes8 are also cross lin3ed over to other E;*'op sets that go to the idea of 8riots8

and 8defaults8. 9he 8defaults8, at least until later in 2016, have the higher level of emotional tone sums.

9he data sets are shoing that 8ide8 and 8ild8 sings in the 8prices8 and 8availability8 of all 3inds of

8formerly plentiful goods8 ill be 8headline nes8 for much of the latter half of 2016. 9he 8ild price

sings8 ill be on everything from 8energy8 to 8foods8 and ill be 8violent8 enough to 8induce localrioting8 in many 8communities8 across the E;*'op. In some of the detail sets e see that 8vital

5household goods8 ill have 8price sings 5due to availability8 of &000 over the course of mere

months.

9he data sets are forecasting that the ;ummer 5northern hemisphere ill be the 8summer of lists8 in

hich 8continuing lists 5of ban3ruptcies8 of 8record brea3ing numbers8 ill dominate all of the media.9hese 8lists8 include 8ne eather records brea3ing 5hich cause food crisis8, 8cities going bro3e8,

8states and counties/parishes going bro3e8, 8national pension schemes going bro3e8, and on and on and

on. 9he 8summer of lists8 is going to be a very large 5ide temporal mar3er for many decades of yet$to$

be$born economists. 9hese lists ill also include huge numbers of 8central ban3s firsts 5and/or mosts8.9hese ne 8record brea3ing central ban3 events8 are all tied into their 8hyperinflationary push8, then the

8putsch against hyperinflation8. It is this latter set hich is more effective from 201 onard that

appears to be the 8driving force8 of the rest of the ne-t 8ten years8. In other ords, a brief, 2/to yearstint of 8hyperinflation8 ill be used 5so says the data as the 8e-cuse8 by 9'9= to introduce 8monetary

reform8 as a 8global issue8. 9hereafter the focus of the data groth is 8humans versus inflation8 as the

8ne global monetary system8 is 8promulgated8.

9he 8hyperinflationary years8 are shoing in modelspace as being the 8orst8 of the 8crushing years 5of

the global depression8 e-cepting if one lives in 4orth *merica. 9he 8death of the dollar8 in its

8purchasing poer8 by the 8cure8 of 8hyperinflation8 is shoing as 8reducing the 8E;*'op8 to a 8shell8 ofits 8pea3 robust self8. 9he data sets are shoing that the 8depression8 ill be 8mar3ed8 by many of the

younger generations as 8beginning8 in 2016. 7ithout regard for the accuracy of the statement the

emotional tone of the 8nation8 ill change from 2016 onard in a palpable ay hich latter dayhistorians as ell as many ho are currently faced ith living through it ill place at the feet of the

Areat Alobal Repression.

9he data sets are shoing that 8crises8 in China ill precipitate a 8de$peg8 as ell as a 8credit rating strip8

and a 8ratings crisis8 hich then spread throughout the 8financial orld8.

It is at this point, some time past Quly 2016, that the 8gold in the vaults8 issue rises, both in the E;* and

in China. Ruring this period the data is forecasting that all media ill be reporting ho 8bad8 and

8orse8 things have become in recent months. Ruring the 8sho me yours and I8ll sho you mine8 phase,

the data shos that the 8numbers8 around 8gold8 and 8silver8 go truly 8ballistic8. 9he data is forecastingthat the 8rate of increase8 of the 8price of gold8 itself ill be increasing at high single digits. ;tated

another ay, the daily rate of groth of the daily rate of groth ill be escalating near ?.

9his 8gold rise rate speed up8 ill be a huge 8catalyst8 for 8lines in the street8 to 8buy physical gold/silver8.

'age 20 of (2



*ll rights reserved


21/32

9he 8desperation8 level seems to be tied directly to the 8rising rate of gold value 5in dollars8. 9he ords

in the media ill include 8spectacular8, and 8parabolic8, and 8roc3et to the moon8, and 8pea3 silver8, and

8pea3 gold8, and 8international currency instability8, and on and on and on.

;tarting bac3 in the near term, e set modelspace to early Qune 2016 and move it sloly through the

year in so doing, the perspective of 8things getting out$of$control$of$tptb8 rises ith each progressive

move toard the end of the year. 9he data sets accrue in larger and larger numbers the further along inthe year e move, and these sets are each groing in emotional sum values as ell. 9he effect of

atching modelspace at this level is to create the impression of a 8big beast dying8 as the core is sloly

consumed by the increasing chaos from the edges.

9he data sets are describing the 8descent8 of the 8daily life8 of the 8average >oe/>osephine8 into a form of

8al3ing 5mentally ounded8 state by the end of the year. 9he hole of the accretion so far for 2016shos a groing 8slide into 5undifferentiated dysfunction8 in hich the 8daily life 5supporting

infrastructure8 goes from its current 8marginally functional8 condition to 8fully fuc3ed up8 by the end of

the year....and that is but the 8near term loer lo8 in so far as longer term pro>ections from the data are

concerned. 9he +9 sets ould have 201J be a 8nasty continuation8 of the 8rottenness8 of 2016.

9he data sets are describing a 8big hump8 that ill be the 8crash period8 of late ;pring and throughout

;ummer. Ruring this period the 8giant lay$offs8 ill begin, as ill the groing 8presence on the street8 of the 8recently unemployed8. 9hese sets are suggesting that 8more and more young people8 are 8ithout

or38, as the 8eather gets hot8 and the 8systems fail8. 9his is the 8gathering8 state of 8milling about8 that

is then 8magnified8 as many of the 8parents8 are also 8fired8, and then 8things 5on the streets get orse8.9he data sets have some details for some areas suggesting that a fe of the 8spar3s8 for this ;ummer8s

8season of contention8 ill include 8an elderly oman crushed don8, and 8ater restrictions 5by police

on street activities8, and 8inner city 5stores shut don 5credit free@e8, and 8hit$and$run by officialdom

vehicle8, and on and on and on...but at the core of all of the upcoming 8social distress8 is the 8destroyedmoney8.

9he data sets are suggesting that many ne 8national scandals8 relating to 8money8 in some form illemerge over 2016 and briefly occupy the 8public attention span8 as the 8ma>or crises8 unfold. ;ome of

these scandals ill include 8gold 5not there8 in hich a 8national E;* pension plan8 hich had

thousands of 8clients8 ho 8thought8 that they had 8gold 5in their %0138 and other 8self directed pension plans8. 9hese sets are suggesting that 8some8 of the 8officials8 at the 8national offices8 of the 8pension plan8

ill 8live/survive to regret8 their 8participation8 in the 8fraud scheme8 as 8clients8 are forecast to 8assault the

offices8 and in the resulting 8confrontation/fight/melee8 several of the 8financial firm employees8 ill 8notsurvive8. 9his is but one of many such scandals. In other detail sets e have descriptors of 8lunch

meetings8 at 8prominent restaurants8 Ked note southern California most li3elyL in hich 8movie people8

ill be 8beaten up/roughed up/dirtied up8 as their 8lunch meetings8 ere ith 8scam artists/sindlers8

ho ill 8happen to be seen8 by some of their 8victims8 and the 8resulting bash$about8 ill 8catch 5movie people8 in the 8video8 of the incident. 9hese sets ould seem to suggest that a 8ma>or celebrity8 ill be

involved and that the 8reports8 of the 8incident8 ill ma3e 8national nes8 for a brief fe days.

ther instances of 8scandals emerging8 are shoing as including 8relabeled foods8 that ill cause

'age 21 of (2



*ll rights reserved


22/32

8huge/giant problems8 ith 8hospitals8 across a 8ide region of the south8. ther issues ill include

8stolen/siphoned funds8 that had been 8converted to money8 and something of a 8national obsession 5for a

fe days8 as a 8chase ensues8, 8felons vanish 5along ith money8, and 8speculative chatter goes cra@y8

until 8resolution8 a fe days later on 8usually empty roaday8 in a 8lonely desert8.

9he longer term data sets have ne groth in areas that are lin3ing =ra@il'op and E;*'op. In much

the same ay that early *merica as temporally lin3ed to the revolution in or 8population movements8 are

underay and ill continue through the 20(0s ith some 8force8. 7hile the data sets have emotionalsum values indicating the usual rise and fall seen ithin all human activities, e have a dominating

floor of emotional tone value to provide support for the idea of 8social cycles completing/changing8 in

hich the cycle is on the order of 8&000/five thousand years8. In other ords, ma>or ma>or changegroing under your feet at a level that you are not able to imagine as it is larger than 8generational8 in

si@e.

9he longer term value sets are bringing in phrases such as 8before the revolution8, and 8in the old days8,and 8in days past8, and 8before the crac3up8, and 8before the brea3up8, and many others all going to the

idea of 8past times8 hen the 8dollar as dominant8. 9hese phrases are shoing as coming into general

circulation over the ne-t 20/tenty years as the E;*'op progresses through its 8decade of struggles8 to8redefine itself8. #uch of the 8redefinition8 effort is shoing as being 8reconciliation8 ith the 8crimes8 of

the 8past 5leadership8 done in the 8name of the people8. *lso it needs to be noted that the 8;audi

officialdom8 is soon going to be 8sha3ing in their robes8 as their 8luc3 runs out8 and the 8bribery ceases tohold8. 7hen this occurs, the 8house of saud8 ill also be under severe stress from its 8emen adventure8,

as ell as 8internal financial chaos8. 9he situation there, in *rabia, is indicated to get very 8intense8 as

the 8*mericans8 discover 8pertinent facts8.

9he data sets are forecasting very challenging times indeed for the ne-t decade and a half. 9he orst of

things are forecast to include 8mass migrations8 as 8nuclear infrastructure8 goes 8bad/rotten8. 9he best of

things are forecast to include 8renaissance8, and 8re$invigoration8 of the populace. =oth of these memesare internally cross lin3ed to each other as the data goes to the idea that 8nuclear disaster8 forces

8creative invention8 at levels 8never before achieved8 all the hile huge parts of the 8population8 go 8al3

about8. *lso please note that the 8diaspora8 sub sets continue to fill ith language echoing that of the1?(08s 8dust bol migrations8.

9here are sets going to the 8renaissance8 in 8american manufacturing8 as the 8ne robotics8 reaches the8brea3 out into the public8 level. 7hat is being forecast here goes to 8shoc38, and 8being overhelmed8 as

the 8robotics concept8 is indicated to be 8torn apart8 by 8american invention8. 7ithin the larger sets in this

segment of the 8renaissance8 e also have the sub sets for the 8ireless telepathy8, and 8other inventions8

that are going to 8severely stress8 the 8control infrastructure8 of 9'9=.

9he E;*'op entity gains ne emotional sums in the areas of both 8anger8 and 8resentment8 as

modelspace is moved forard over ;ummer. 4ot only from the 8economic malaise8, and the 8politicalgames8 being played by the 8party structure8, but no, also shoing as a cause is the 8degradation8 and

'age 22 of (2



*ll rights reserved


23/32

8dysfunction8 of the 8electrical grid8. *s the 8grid8 begins having 8regional problems8 the data shos that

8anger8 ill 8manifest8 in 8do@ens8 of ays as the 8population8 5in the affected areas are 8forced to react8 to

8blac3out conditions8 >ust hen they need the 8electrical support8.

* number of sub sets are painting a picture of the 8ne monetary system8 that ill be 8rising8 as the

8dollar infrastructure dies8 here in E;*'op. 9he data currently is shoing an 8evolving system8 that is

not 8top don8 and 8delivered8, but rather is 8born of necessity8 and is 8self organi@ing8 and 8self limiting8.#uch of this language goes to increasingly 8sophisticated 5forms of barter8, but also crypto currencies

are prominent in the descriptor sets as being a 8mobile alternative8 to 8daily 5degradation of the dollar8.

#any other sets are related to the 8dollar degradation8. 9hese include 8cruise ship labor disputes ith

passengers held hostage8 8hospitals closed due to lac3 of supplies8 8public events canceled due to lac3

of funds for police/security/cleanup8. 4ote that this last is going to 8anger8 a hole lot of people hoill decide to 8do it anyay8 that in turn leads to some very 8bad outcomes8.

BritainPop

9he data sets are shoing that =ritain'op is going to be 8sad and drun38 as a result of yet another8crushing defeat8 to the 8population8 at the 85metaphoric hands8 of the 8controlling elites8. 9he data is

shoing that 8migration8, and 8e-tremist behavior8 are amongst the top motivators for the =ritish'op intheir 8voting8, and further the data suggests that their 8ill shall be ignored8 very shortly after the

8political sham8 of the 8vote8 has 8cooled8.

IsraelPop

!ecent data sets are shoing that the 8declining living standard8 amongst Israel'op ill produce8economic schisms8 as 8various fronts 5political interests8, sensing a 8developing poer vacuum8, ill be

8pressing their case8. 9hese data sets are filling ith ne supporting sets for a 8governmental push8 to

8produce robots 5general purpose8 that ill be the 8big emotional hoo38 for the 8corporate base8. 9he problem is going to be that >ust as the 8effort 5to boost local economy via big debt funded investment in

robotics8 begins, the data is forecasting that a 8scandal8 ill be 8developing8 over 8robots gone bad8. In

the instances cross lin3ed the data suggests that there ere 5ill have been 8fatalities8 and 8corporate

cover ups8.

BrazilPop

*s had been forecast in ay long ago *+9* reports, the 8revolution8 meme has surfaced in =ra@il. 4e

groth shos this 8revolution8 meme spreading across the continent from east to est and starting in

the middle, spreading first north, then later to the south. =oth Eruguay and 'araguay seem relativelyimmune to the upcoming 8problems8 or 8upheaval8.

Current groth in the =ra@il'op sets include the idea that 8international8 problems are going to 8erupt8

'age 2( of (2



*ll rights reserved


24/32

along ith =ra@il'op. 9he idea coming out is that all manner of 8international sporting events8, not only

the lympic Aames, are going to be 8shut out8 of 8production facilities8 by 8local social action8 hich

ill emerge from a 8riot gone ild8 that ill become a 8successful model8 for 8local popular actions8. 9he

data sets are forming support for a 8occupation @one8 hich ill really be a 8no$go officialdom @one8 dueto the 8many local committees 5forming ne local governments in a de facto fashion8. 9he idea is of a

=ra@il 5from the vie of officialdom being 8cratered8 as various 8local communities8 begin reali@ing

they are 8isolated8 and 8not li3ely to receive 5federal government assistance8. 9he data further supportsthe sets that have language indicating that 8to spea3 is to secede8, or 8public outcry8 over 8incompetence

and corruption8.

ther sets related to the 8revolution8 sub set ithin =ra@il'op include 8starving 5hunger stri3esM8 related

to 8prisons8, and 8ports shut don 5as credit free@es due to international >itters over local popular

actions8.

9he 8local popular actions8 are e-tensively cross lin3ed over to the 8alternative media8 and hat is called

8oo$oo8 5or the officially denied, and/or disappeared information8. 9he data further suggests that due

to 8economic lies8 the 8local population8 is 8forced8 to 8investigate 5hat happened to them, their >obs, etcetera8. 9his is shon as 8creating conditions8 for 8mass aa3ening8. 9his is going to be 8hastened8 by

the 8ave of ban3ruptcies globally 5that creates histle$bloers in large numbers8.

Markets

9he =IA 4F is shoing up in the #ar3ets entity as the ne data is accruing for the 8largest 5paper

debt crash ever8. 9he 8=IA 4F8 crash language is piling up ne aspect/attribute sets for 8euity

plunge8 and 8stoc3s plummet8, and 8debt defaults8, and 8carry 5fore- trade failures8, and 8pricefluctuations8 in 8bonds8. 9he data is groing in the sets for a 8stoc3/euity mar3et movement8 that is

described as 8bringing tears8 and 8suee@ing 5the boels8. 9he data is filling ith language around the

idea of a 8record pace 5donard8, and 8elevator stomach heaves8. ther sets sho that 8corporations8ill be 8scrambling 5to recover mere pennies8 as 8liuidity goes/fails8.

9he language around 8liuidity8 continues to gain supporting sets for 8supply chain 5credit failure8, and

8base money supply vapori@ation8, and 8ithering arteries 5lead to shrin3ing veins8. ther ne sets

include 8gateays 5thin8, and 8fat 5over an-ious credit pushers8 and 8no 5credit demand8. 9he datafurther shos that the 8collapsing credit demand mar3ets8 as ell as the 8disappearing base money

supply8 ill produce a maturing situation over ;ummer and through ust in time delivery system8 is described as 8falling apart 5as though fasteners removed8.

9hese and many other ne sets are describing a 8orld gone on3y8 according to the 8officialdom8 vieof things. In this 8orld gone on3y8 viepoint, the 8officialdom pronouncements8 are supposed to be

the 3ey element in determining ho things or3, not 8reality8. 9he 8impact of reality8 is forecast as8shoving a stic3 5up the ass/arse8 of 8officialdom8 as the 8mar3ets and liuidity failures8 ill 8prompt8 an8officialdom response8 that ill 8totally scre up 5the situation8. 9here are several ne sets going to the

idea that the 8


25/32

8unell8 and in a state of 8un$reality8.

9he 8un$real8 feeling of the 8mar3ets8 is shoing as being a 8factor8 in and of itself as 8disbelief8 becomes

both the 8feeling8 and the ord heard in both mainstream propaganda and alternative press any time the

8mar3ets8 are being discussed. ther ords to be heard relative to the 8mar3ets8 over the rest of *pril andthrough #ay/Qune are 8tilted8, 8s3eed8, and 8suirrelly8. ther images coming up are comparisons to

Ocaged rats eating each others8 tailsP and 8buc3ets 5of pissed off octopi8. 9he data sets are seemingly

indicating that the 8disbelief8 of 8officialdom numbers8 about 8anything8 ill be reaching such large proportions of the population that a 8revolutionary aa3ening8 is being forecast as 8on the hori@on8. Insailing terms, this phrase means that 8something, once observed in the distance, ill continue to gro

daily in your vision8.

9he data sets are shoing that the 8hyperinflation8 that is forecast to begin in mid to late ;ummer

5northern hemisphere ill be described by the 8captive press 5a3a mainstream propaganda press8 as

being 8but an episode8, hoever, the 8impacts8 are forecast as 8hitting or3ing population8 to such ane-tent that the 8population8 ill 8feel blooded8 by the 8cutting 5of the money8. 9hese sets are further

supported by ne sub sets that are accruing to the older supporting sets of 8food crisis8, and 8failures of

5delivery system8 that ill be 8episodically 5floating about 5the E;* 5and many parts of Canada8.

9he data sets are suggesting that the ord 8great8, and 8giant8, and 8monstrous8 ill be some of the many

ords in the same vein that are forecast to be 8pouring out of8 the propaganda press over these ne-t fe

months. 9hese ords are going to be applied to 8bubbles8, as ell as 8aves 5of selling8, and 8days 5ofdon numbers8. 9he data sets are pointing toard the 8*pril fall off 5of the edge8 of 8moneti@ing of

assets8 that ill be 8preceding ;ummer 5northern hemisphere hyperinflation8.

ther ne sets for 8popular culture8 ords/phrases include a forecast for 8all$in8, and 8actual costs8 as the

8price suppression8 that has been occurring as a result of 8central planning8 accelerates its 8peeling bac38

of the 8layers of rigging8. 9he data sets are suggesting that 8mar3ets8 of all 3inds ill be entering a 8chaos period8 that ill dominate the 8summer broadcasts8 ithin the 8estern media8.

9he data is suggesting that by late in ;ummer 5northern hemisphere, the outbrea3 of 8hostilities8, as

ell as the 8environmental destruction8 that is starting to emerge from the 5by then 8recent sin3ing8 ofsome form of 8transport ship5s8 ill be the 8named cause8 for the 8raging8 and 8terrifying8 emergence of

the 8global currency crisis8.

9he data accretion patterns are shoing that the 8brea3 don8 of the 8mainstream propaganda press8 ill

be accompanying the 8aterfall crash5es8 of the 8global fiat currencies8. 9he data is shoing that

8bi@arre schemes8 ill be 8paraded 8 by 8government shills and spea3ers8 in front of the 8populations8 asthey 5officialdom tries to 8get something to fly 5be accepted8.

9he data accretion patterns are arguing for a 8derivative hot potato8 to emerge in late #ay or early Qunethat ill set 8fire to ban3s8. ;ome (0S per cent of the ne 8fire to ban3s8 language has both 8gold8 and

8silver8 ithin the ne groth for the sets. 9hese ne 8silver8 and 8gold8 references are themselves

descriptor sets for sub sets ithin this le-ical structure. 9he gold and silver sub sets ithin this area are

'age 2& of (2



*ll rights reserved


26/32

filling ith 8money8, and 8interest rates8 as primary and secondary supporting aspects. 9he attribute sets

ithin these aspects are focusing on 8competition8 beteen 8ban3s8 to 8acuire8 and 8store8 these forms of

8real money8. or contributing sub set

for the 8derivatives hot potato8 ith a focus in these sets on a 8debacle8 that ill begin ith or in 89ur3ey8that ill 8damage8 a 83ey element8 that is a 8basis8 for a 8derivative chain8. 9he real problem being

highlighted is that a series of 8beteen ban3s8 sales of 8derivatives8 ill be discovered to be a 8tightly

bound chain8 that ill have the 8holding lin3 brea38 QE;9 as the 8ne-t leg8 of the 8currency competition8 begins its 8biting 5to the bone8 phase.

9he ne data for this report brings in ne sets for 8hyperinflation8 that ithin their supporting sets theyhave ne sets shoing a 8forced 5revaluation of gold8. TTT 4ote, this may be >ust discussion 5at this

stage and not action. 9here are some hints that this is a 8thing U5meme8 being driven by 9'9=. 9here

are a number of large, ne cross lin3s forming that terminate ithin the 9'9= entity here theterminating sets are filled ith ne language for 8ne limits8, and 8ne understanding 5of gold 5in

monetary policy8, and 8no constraints/bounds 5on the currency devaluations8. ther sets are directly

going to 8ideology8, and 8fundamental belief8, and others in a similar vein that go to the 8religious8 nature

of the 8monetary system8 5ie belief in 8ephemeral abstractions/mental images8 that ill be 8rearing up8 inthe discussions about 8gold8 5specifically.


27/32

shos that they do not merely deflate, but rather 8rupture8 and 8e-plode8 in a 8violent8 manner.

Housing ithin the data accumulated over these last several months is forming an entirely ne

narrative about the future of both 8housing8, and 8construction8 across the globe. 9he #ar3ets entitycomponent of the 8housing shift8 is shoing that a 8condition8 of 8euity8, but 8no cash8 is going to 8assailt8

the 8real estate mar3ets8 globally as the 8estern 5dollar dominated financial system8 come further

8unglued8 over this ;ummer and into or mar3ets8 in the 8estern orld8.

9here are ne groth areas in the 8abandonment 5of high end property8 as the 8high pay or3ers8 get

8trashed8 by the 8crumbling system8 and 8discover8 that they are 8not rich8 but rather are 8debt bound8.

#any of these properties ill be 8abandoned8 hen the 8euity8 starts 8melting aay8 in the 8degradingreal estate mar3ets8.

9hen, curiously, there are several sets indicating that a strange development ill occur in hich 5li3ely

in E;* 8government agencies8 ill be 8investigating8 the 8sudden 5rectifying donard turn8 of their8real estate mar3ets8 as 8manipulation8. 9his is indicated to form a bit of 8comedy8 for those ho are

aare as these 8government agencies8 start 8attac3ing8 the 8issue of manipulation8 only to 8run into ban3s8.

9his ill create a 8histle$bloer8 ho is indicated to 8change8 the 8game 5of mar3ets corruption8.*pparently this individual is going to 8bring 5don8 the 5at that time Otop to ban3 ceo8s O. *gain,

'age 2J of (2



*ll rights reserved


28/32

curiously, this 8histle$bloer8 event is also indicated to be used 8in far far future8 as a 8temporal mar3er8

for the 8failure8 of our current 8monetary 5financial system8.

9he data sets from this point are shoing that 8comple- deals8 ill be 8coming apart8 in a 8flood8 over2016 such that 201J is also filling up ith temporal mar3ers, including the 8total collapse 5of the

global mar3et 5for mortgages8.

#any of groth areas of the #ar3ets entity are fundamentally pointing toard a 8comple-ity 5pressure

systemic failure8 in hich the combining factors of 8failure8 at 8small levels8 5mainly ithin officialdom

ill lead to a situation of the 8bro3en teeth8 ill be 8bloc3ing 5the movement 5of the gears8. 9he data isindicating that the 8failures8 at small levels have already accumulated to the point of being 8system

clogging debris8. 9he 8comple-ity8 component of the upcoming 8failure bloc3age8 needs to be

recogni@ed as the contributing factor hich 8pushes the system 5over the edge8. 9he 8comple-ity8 of the8interconnected systems8 that are the 8mechanisms8 of 8government8 become so 8ound up together8 as to

8cease8 to 8function8. ;ome of the details include 8tourists8 being 8held hostage8 by 8par3 or3ers8, and

8boats8 being 8denied landings8 due to 8computer failure8 hich in its turn induces 8port or3ers8 to

8protest 5lac3 of or38 hich then causes the 8police8 to 8arrest the port or3ers8, and in the melee, alsomany of the 8port authorities 5management8 also end up in >ail. 9his is li3ely going to be in the E;*,

but the immediate impact ill be to cause 8international 5shipping ramifications8 and a 8rapidly

unfolding 5trade ar8.

#uch of the 8comple-ity bloc3ing8 story ithin the data sets goes to the idea of 8policies8 being

implemented hich are 8instantly8 in conflict ith 8reality8 and 8sanity8, and also, freuently, 8other insanegovernmental policies8 hich e-ists as 8no 5policy8 is 8ever revieed8 nor 8uestioned8 prior to

8implementation8. 9his is described ithin the data as a 8off shoot8 of the 8comple-ity problem8 also

8affecting policy creators8 and 8implementing personnel 5a3a police8. ;ome of the 8comple-ity8 set has

brought in ne sub sets to the effect that the 8officialdom8 ill find itself in 8daily conflict5s 5beteengovernment agencies and departments ith itself8.

* number of ne sets are bringing in language for the #ar3ets entity that are in support of a very primary emotional descriptor of 8distortions8. 9hese ne sets are adding more eight to the 8obble8 of

the 8dollar8, 8pumping the pendulum8 so to spea3, as the data brings in ne sets forecasting 8regional

5ithin E;*8 separations at the 8government level8 due to 8dollar purchasing poer failure8 and8regional source dollar generation8.

In other language, the description of the 8E;* governmental infrastructure8 during a period of8officialdom induced meltdon8 is going to resemble 8feuding arlords8, and 8gang turf battles8. 9hese

8intergovernmental battles8 are shoing as being entirely about 8retaining funding8 and 8poer centers8.

*s the 8government8 is shon 8fighting it out 5amongst themselves8 for 8crumbling funding8, the#ar3ets entity is painting a picture of 8chaos8 and 8disruption8 in the 8flo of finance8 and the 8trading of

goods8. 9he data sets continue to accrue for a 8very bad summer and fall8 leading to a 8terrible inter of

5financial death8 here in the #ar3ets realm. 9hese sets are forecasting that the 8financial blac3 plague8ill be emerging in early ctober as 8record numbers 5of corporations8 ill be 8going out of business8

'age 2 of (2



*ll rights reserved


29/32

and/or 8filing for ban3ruptcy8.

*s modelspace is progressed through ;ummer and into ust in time delivery systems8 to all 8pile onto8 the 8population8 suchthat not only the 8conditions for riots8 but also the 8conditions8 for 8regional economic collapse8 to occur.

9hese sets are cross lin3ed internally over to the 8real estate mar3ets8 sub set shoing that 8high end

properties8 ill be both 8abandoned 5in the early stages8, and 8suatted 5by former 8oners8 in latterstages8 of the 8Areat !eal Fstate Crunch 20168. 4ote the 8real crash8 ill be in 201J.

#uch of the language ithin the 8bonds8 and 8real estate8 sections are going to the idea that a 8crisiscondition8 e-ists no, that is basically a 8super huge planet si@ed bubble8 that is going to 8start to pop8 in

;ummer 2016, and ill ta3e over a year to actually 8complete the e-halation of the balloon8. 9he data

sets are shoing that the 8si@e of the balloon8 ill be 8debated8 as it is 8failing8.

9he data sets are continuing groth in the 8hyperinflation8 sub sets that ill be 8led by the


30/32

picture vie of the 8financial8 year ahead emerges. In this year, e have the data sets forecasting the

8shoc3 of the ne8 as 8officialdom8 reaches its on 8crac3ing point8 here in the 8financial facade8 is 8set

aside8 to 8deal ith reality. 9hese sets at this larger, more national/social/cultural level are forecasting

that 8governments8 ill be 8getting ise8 and 8reacting to 5developing reality8 in such areas as 8silver8 and8gold8. In the case of the latter, the 8officialdom8 is described as going to 8great lengths8 to 8disparage

gold8 during the 8upcoming hyperinflation8, hoever during that same period, the same 8governments8

ill be 8screaming8 to 8protect8 their 8national assets8 of 8silver hoards8 as 8silver8, across the globe, shiftsfrom 8industrial$monetary8 into 8strategic$monetary$industrial8 status. 9hese sets are shoing that

8surprising movements8 in the 8price8 ill actually be so 8violent8 as to 8precipitate heart attac3s8. *nd the

emotional sums in this area are but a small fraction of hat is being carried by the longer term valuesfor the 8ne-t 10/ten years8. 9hese sets are filled ith language for 8too precious 5to use up8, and

8strategic embargo 5on shipping silver out side of borders8, and many other sets going to the idea of

8those ho has it, ants to 3eep it8 at a national level relating to 8silver8.

9he data sets are filling ith e-amples of 8contradictory behavior8 especially as it 8issues from

officialdom8. 9hese sets in all entities are going to the idea of 8behavior8 in 8conflict8 ith 8itself8 from

8local and state government8 to 8international agreements8 in hich 8section *8 ill 8disagree8 ith8section B8. 9hese many 8conflicts8 are going to be part of the 8developing governmental sei@e$up8 in

several nations as 8government8 reaches a 8pea3 of affordability8 and 8capacity 5to function8. 9his

developing trend is very pertinent to the 8trading community8 globally as a great many 8governments8 aregoing to become so 8impeded8 and 8constipated8 as to 8cause 5internal to their countries mar3ets8 to

8misbehave8.

SpaeGoat!arts

9he 8outspreading8 of the 8personal technology revolution8 is shoing as accelerating over ne-t fe

years ith several 8announcements8 coming this ;ummer 5northern hemisphere. 9he data is forecastingthat 8ne refining 5electrical separation of elements from aggregates8 ill be one of the announcements

hich is in a direct line to the upcoming technology 5fe years out in hich 8smart 5refining bots8 ill

8slide don veins 5of ore8 and 8electrically e-tract 5the minerals8. 9his first announcement is shoingas being 8very underhelming8 to the globe in general, but e-citing huge interests among 8physicists8and 8ma3ers8.

ther sets in the ;paceAoat


31/32

;paceAoat


32/32

in Class VI temporal aters. 9ighten your grip on reality, it is your only paddle on this e-treme and

e-ploratory trip. !apids dead ahead. Weep your its about you rescue I; impossible.

'age (2 of (2


Class VI !escue Impossible " #ay 2016

Documents

Alta 2016 April WEBBOT CLIFF HIGH