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Location: UFOUpDatesList.Com > 1999 > Feb > Feb 2

Open Letter: MJ-12 & Dr. Wood

From: Stig Agermose <stig.agermose@get2net.dk>
Date: Tue, 02 Feb 1999 03:39:24 GMT
Fwd Date: Tue, 02 Feb 1999 12:59:23 -0500
Subject: Open Letter: MJ-12 & Dr. Wood


Source: "alt.ufo.reports".

Stig

***

From: "Sid Fiber" <dataVoid@hotmail.com>
Newsgroups: alt.paranet.ufo,alt.ufo.reports
Subject: Open Letter: MJ12 & Dr. Wood
Date: Mon, 1 Feb 1999 16:49:58 -0800


(Background: This is an open letter to Dr. Bob Wood and his son
Ryan Wood who are attempting to authenticate the validity of the
MJ-12. These documents allegedly document the US government's
efforts to conceal the discovery of extraterrestrial beings and
crafts during the 1940s.)

Dear Dr. Wood--

If Truman, Bush, Einstein, and others authored the Majestic 12
documents, then the methods of forensic-linguistics will
conclusively prove it.

Several years ago, Dr. Donald Foster of Vassar College devised a
brilliant statistical method for determining the authorship of a
document that he has since applied in dozens of court cases
requiring verification of document authorship. In 1996, Foster
successfully pegged Joe Klein as the anonymous author of Primary
Color, the tell-all White House novel. Also, at the request of
the FBI, Dr. Foster conclusively verified that Unabomber suspect
Ted Kaczynski had indeed authored his invective manifesto.

Foster first gained prominence by successfully applying his
technique to solve an age old mystery surrounding the acting
roles of Shakespeare. His breakthrough--hailed by Elizabethan
scholars and computer scientists, alike--was to assume that even
Shakespeare was prone to linguistic habits which revealed
themselves through statistical comparison. Please read the
following article for details.

Clearly Dr. Wood, if you were to apply Dr. Foster's technique to
the MJ-12 documents, you will be a giant step closer to
conclusively verifying the authorship of these intriguing
documents. If you're interested, the following article contains
further details about Dr. Foster's work.  You can contact him at

foster@vassar.edu

or call Vassar at extension x5634. Thank you and good luck.

--Sid Fiber


>From the book "Interface Culture, How New Technology Transforms the
Way We Create and Communicate"

By Steven Johnson

pg. 155 - 260

Can a machine make sense of language without learning how to read? To
answer that question, we need to venture back to one of the enduring
mysteries of Shakespearean scholarship, a mystery that was solved by
the statistical analysis of digital technology. Of all the arcane
puzzlements of Elizabethan literary criticism, few have been as
tantalizing, and elusive, as the details of Shakespeare's acting
career. For generations, scholars have known conclusively that the
Bard performed in every play that he wrote; in two plays, in fact, we
know which parts he played: the ghost in Hamlet and Adam in As You
Like It. His other roles, however, remain a mystery. Because records
of the Globe Theater's production schedule have survived through the
ages, we know the run dates of each play in the oeuvre. We also have a
reasonably accurate chronology for his writing career, which means
that we can gauge with some precision the overlap between performance
and composition. In other words, we know that Shakespeare was writing
King Lear while he was acting in Othello, and that he was acting in
The Merchant of Venice while he was writing Henry IV we just don't
know the parts he was playing at the time.

Or at least we didn't know until Don Foster stumbled across a
brilliant, and strangely reassuring, idea. If Shakespeare had indeed
memorized the lines for a part in one play while composing the script
for another, then perhaps there had been a little seepage between the
two. Perhaps the ritual of performing every night had lodged certain
words in Shakespeare's head, like the detergent jingle from morning TV
that hounds you through the workday. Anyone who writes for a living
will recognize this phenomenon immediately. Words cycle through our
daily vocabulary at different rhythms. Certain words stick with us for
life, and remain immediately accessible to us at any moment: the names
of loved ones, the building-block grammar of our native tongue, the
primary colors and cardinal numbers, and so on. Other words wax and
wane, in sync with forces larger than the individual speaking them:
the fashionable vagaries of slang, the geek-speak of technological
innovation, the "ethnic" idiom derived from broader demographic
trends. (Think of the influence of black English on the mainstream
American dialect over the past twenty years.) Most words, however, lie
somewhere in between: drifting in and out of our regular vocabulary,
like a band of itinerants cursed with a hankering to settle down. The
word profound strays into your head and sits there for weeks, at the
very edge of consciousness, primed for use. And for weeks, whenever a
situation arises that demands a tone of seriousness or intensity or
ironic overstatement, the word profound rolls out like clockwork. But
soon enough another contender implants itself (major, let's say, or
crucial), and profound retreats to the darkened wings of occasional
use.

Foster's breakthrough was to assume that even the great Shakespeare
might be prone to the same linguistic habits. Was it possible, Foster
asked, that words from Shakespeare's memorized lines were accentuated
in the Bard's vocabulary during the run of each play? Could the
language of Shakespeare's acting career have infected his play
writing? It took a computer to answer the question, a computer
specially programmed to track Shakespeare's use of statistically
meaningful words, words that he used fewer than ten times in his
career. The computer analyzed the distribution of these words on two
levels: first, their appearances in individual parts (Hamlet's ghost,
say, or Midsummer's Lysander); and second, their appearances in entire
plays. If Shakespeare the actor was influencing Shakespeare the
playwright, then certain plays curve; instead, progress happens in a
nonlinear, staggered
fashion, with steady, incremental growth punctuated by  sudden leaps
forward. Take a bowl of water and gradually lower the ambient
temperature in the room; for a stretch of time, the change is linear:
the water gets colder as the temperature drops. But at a certain point
a threshold is crossed, in this case the threshold of zero degrees
Celsius, and suddenly you have not colder water but ice, a new
property, fundamentally different from the preceding one. A slower
machine, equipped to handle less textual information, is nothing more
than a literary bean counter good for generating a concordance for a
single document, but not terribly sophisticated otherwise. But ramp up
the processing power significantly, far enough to do a comparative
study of word use in hundreds of documents, not just one, and you hit
a threshold point, a singularity. The number cruncher becomes a
literary sleuth, outsmarting tenured professors and armchair
Shakespeare buffs. In his Atlantic article, Dolnick speculates that
Foster's software is a "sign of things to come" for literary studies.
But the promise of literary computing extends well beyond the obscure
details of Elizabethan drama. By the end of the decade, most personal
computers will sport a version of Foster's program as a basic tool in
the human interface, as essential to the user experience as windows
and icons are today.

Perhaps the most startling thing about the Foster study is the
simplicity of the program he used. The statistical properties of
language, after all, are not limited to word frequency. There are, in
fact, hundreds of attributes that the computer can use to build a
numerical model of a given text. Which properties you decide to track
depends on what you're looking for. Let's say you're trying to gauge
the relative complexity of a document - would be littered with the
vocabulary from a part in another, earlier play. The scattering of
high-information words would be so light and varied as to be
unnoticeable to humans, but the computer's prodigious
pattern-recognition skills would track it down in a matter of hours
assuming, that is, that Foster's hunch was correct.

The results that came back from the lab turned out to be as
precise and clearly defined as a fingerprint. Each play
possessed a mirror-role in another play, revealed by the shared
idiom of high-information words, like a family of orphans
reunited by the science of DNA testing. In each instance the
overlap followed the chronology of performance and composition.
The results actually exceeded Foster's expectations. The
analysis, as Edward Dolnick reported in The Atlantic, could be
confirmed from a number of different angles: "It never assigns
to Shakespeare a role we know another actor took. The roles it
does label as Shakespeare's all seem plausible male characters
rather than women or children. The test never runs in the wrong
direction, with the unusual words scattered randomly in an early
play and clustered in one role in a later play. On those
occasions when Foster's test indicates that Shakespeare played
two roles in a given play -Gaunt and a gardener in Richard II,
for example - the characters are never onstage together."

Using only the limited tools of word counting, the computer had
solved a mystery that had eluded sentient, English-speaking
scholars for centuries. The sterile number crunching powers of
the PC could now tackle more rarefied, nuanced problems,
problems that had as much to do with the meaning of language as
with its statistical base. Once again, we see evidence that
technology rarely advances along a steady You could have the
computer monitor the length of each sentence; you could measure
syntactical intricacy by tracking the 1 number of clauses
separated off by commas, em dashes, colons, 8 and semicolons.
Simply calculating the average letters-per-word would probably
be enough to differentiate, say, The Cat in the Hat from Minima
Moralia. A combination of all three might be sufficient to
generate a useful complexity ranking for text documents.





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