// OPEN INTELLIGENCE — PUBLIC ARCHIVESYNTHESIS ENGINE · CORPUS 38.87°N 77.05°W
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DISCOURSE INDEXA MACHINE READING OF THE DISCOURSE
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DOCS
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// THE FIELD'S COLLECTIVE VOICE, MACHINE-READ

SYNTHESIS

A machine reading of the field's collective voice — thousands of hours of testimony, declassified files, peer-reviewed papers and archival records, with every attributed claim extracted and mapped where the discourse agrees, splinters, and shifts.

We index what sources say, not what happened — every figure a resolved count, weighted by how independently a claim recurs.

HOURS ANALYZED
0
1,055 VIDEOS TRANSCRIBED
SOURCES INGESTED
0
1,055 VIDEOS · 9,701 DOCS
CLAIMS EXTRACTED
0
ATTRIBUTED & GRADED
RECURRING DETAILS
0
TRACKED ACROSS THE ARCHIVE
STRONG LINKS
0
DETAILS THAT APPEAR TOGETHER
02 / THE FIELD MAP

How the details connect

Each dot is a recurring detail that keeps coming up in the reports — a shape, a being, an effect. Dots are grouped and coloured by theme; a line joins two details that tend to show up together, and the heavier the line, the stronger that link.

⤢ BIG PICTURE
FR-SYNTH · WHICH DETAILS APPEAR TOGETHER
SIGHTINGSBEINGSABDUCTIONCONSCIOUSNESSDISCLOSUREPHYSICAL EFFECTS
DETAILDISCLOSURE

Multiple witnesses

Comes up in 1,418 reports — about 24.8% of cases in the archive (give or take a little). It's strongly linked with 27 other details that tend to show up alongside it.

SEE TAGGED CASES →
HOW OFTEN IT COMES UP24.8%
SHADED BAND = OUR MARGIN FOR ERROR (17.233.6%)
COMES UP IN
1,418 reports
STRONGLY LINKED TO
27 details
OFTEN SHOWS UP WITH
03 / BY GROUP

Pick a group to explore

Each group gathers related details. Choose one and the “most common” list below narrows to just that group.

04 / MOST COMMON

The details that come up most

65 details across every group, ranked by how often they come up.

#DETAILHOW OFTENLINKS
— = NO PAIRING CLEARS THE SIGNIFICANCE BAR (FDR q < 0.05)
05 / HOW IT WORKS

How the archive is built

From raw sources to the maps and rankings on this site — the same steps, applied to everything, with nothing asserted as true.

OUR OWN ANALYSIS ENGINEPurpose-built, not off-the-shelf — machine reading plus custom statistics, applied to every source the exact same way.
01INGEST

What goes in

Interviews and documentaries, declassified government files, peer-reviewed papers, news and archives — pulled in and transcribed word-for-word.

10,756
SOURCES GATHERED
02MACHINE READING

We read every word

Our language models read every source against the same template — pulling out each claim, who made it, where, when, and what they described.

11,009
CLAIMS PULLED OUT
03RESOLVE & SCORE

We connect the dots

Our own statistical models merge duplicate accounts into one case, weigh how independently it recurs, and test each pattern against a control.

3,806
CASES PIECED TOGETHER
04MAP & RANK

What you see

Everything is graded, ranked and mapped — the field map, case files, timelines and studies on this site — never asserted as true, only counted.

65
RECURRING PATTERNS MAPPED