Seasonal Sightings Analysis

Origin & History

This analysis did not begin with a theory about what UAPs are. It began with a much narrower, testable question: does the widely repeated claim that UFO sightings “peak in summer” actually hold up against the full historical record, and if it does, why? The National UFO Reporting Center (Robert Gribble's NUFORC, founded in 1974 and directed by Peter Davenport since 1994) is the largest continuously operating civilian UFO sighting archive in the world, and The Omni Ledger's live sightings engine indexes its complete public dataset — 147,585 reports spanning 1906 to late 2023 — as the backbone of both its Sightings DB search tool and its interactive UAP map. Because that dataset already existed inside the site's own infrastructure, it became possible to ask the seasonality question rigorously: not by sampling or estimating, but by running direct programmatic queries against every single record.

The Omni Ledger Research Team ran fourteen separate analytical queries against the live database: sightings by month, by day of year, by hour of day, by shape category, by U.S. state and Canadian province, by decade, by reporting era (telephone-hotline era versus internet-form era), by observer count, by meteorological season, by night/day ratio, by fireball–meteor shower correlation, by summer/winter ratio per jurisdiction, by year-over-year July share, and by historical wave-year breakdown. Published June 30, 2026 as an original Omni Ledger data-journalism exclusive, the resulting analysis corrected several long-standing assumptions about the archive, exposed two distinct epochs in the dataset's own reporting history, and isolated a small number of statistical anomalies significant enough that no available behavioral explanation currently accounts for them. The eleven findings below, together with the shape–season matrix and the historical wave-year breakdown, are presented in the order the underlying queries build on one another — establishing the baseline distribution first, then progressively subtracting the effects that can be explained (fireworks, meteor showers, the internet-era reporting shift, latitude) to see what, if anything, remains.

Scientific Foundations & Methodology

All fourteen analyses in this study were run directly against The Omni Ledger's live sightings database, which loads and indexes the complete NUFORC dataset at server start. The same data powers the site's Sightings DB search engine and interactive UAP map. Every figure cited anywhere in this article is derived from a direct programmatic query — no manual counting, no sampling, no extrapolation.

The NUFORC dataset (National UFO Reporting Center, nuforc.org) contains 147,585 reports spanning 1906 to late 2023. Each record contains date, location, shape, duration, observer count, hour of sighting, and summary text. The dataset represents civilian self-reported sightings filed via telephone (pre-1996) or web form (1996–present) under the administration of Peter Davenport (1994–present) and originally Robert Gribble (founded 1974). Approximately 6,200 records predate the 1996 internet era; the remaining 141,385 are internet-era filings.

Known limitations: NUFORC represents self-reported civilian observations only. It excludes military encounter data (much of which appears in The Vault’s declassified government records), foreign-language reports filed with non-English reporting centers, and sightings never reported. The dataset has systematic underrepresentation of rural areas, non-English-speaking communities, and events predating mass internet access. Independent peer-reviewed work has reached compatible conclusions about the dataset's behavioral character: a 2022 study in Physica A modeling the statistical dynamics of NUFORC reporting found the reporting process itself, not just the underlying phenomenon, drives much of the temporal structure in the archive, and a 2023 Scientific Reports study of 98,000 U.S. sightings (2001–2020) found sky-view potential — light pollution, tree canopy, cloud cover — and proximity to aircraft traffic were statistically significant predictors of where sightings cluster, independent of any claim about the phenomenon itself. This dataset should be treated as a record of reporting behavior about the UFO phenomenon, not a census of the phenomenon itself — a distinction that runs through every finding below.

The Baseline: What the Full Distribution Actually Shows

Before examining individual anomalies, it is essential to establish the actual distribution of all 147,585 reports across the twelve months of the year. This is the foundation every other finding in this analysis rests upon.

The uniform monthly expectation — if sightings were distributed without any seasonal pattern — would be 8.33% per month. July exceeds this by 4.29 percentage points. February falls short by 1.46 points. The spread from trough to peak is 5.75 percentage points — not a marginal difference, but a systematic signal that demands explanation across multiple dimensions.

June through October — five consecutive months — collectively account for 50.77% of all sightings while comprising only 41.6% of the calendar year. The other seven months share the remaining 49.23%. This is a pronounced skew, and its causes are layered: some behavioral, some technological, some genuinely unexplained.

July 4th: The Single Biggest Sighting Day in All of Recorded History

Of all the findings in this analysis, none is more striking in its raw numbers than this: July 4th, accumulated across all years in the NUFORC database, is the single highest sighting day of the entire year by a wide margin.

The July 4th number is extraordinary. The typical non-artifact day in July averages approximately 480 sightings across all years. July 4th generates 2,167 — 4.5 times the daily average. July 1 (899) is itself elevated, almost certainly because Canada Day produces fireworks across Canadian cities simultaneously, and Canadian reports constitute a significant fraction of the NUFORC archive.

The first week of July as a whole is deeply distorted:

That 67% multi-witness rate for the July 1–7 window is the highest of any comparable week-long window in the dataset — and it makes intuitive sense. Fireworks events are communal. Families and crowds watch the sky together. When a genuine or ambiguous object appears among fireworks, multiple observers report it simultaneously. This inflates the multi-witness count without necessarily indicating higher-credibility sightings — in fact, the opposite may be true: fireworks create the most cluttered, visually complex sky of the year, making accurate identification hardest.

The August 12 entry (685) is also significant: it is the peak of the Perseid meteor shower, one of the most reliably visible annual astronomical events in the Northern Hemisphere. Its appearance in the top-10 calendar days is direct confirmation that meteor showers generate measurable UFO report spikes, a finding examined in depth below.

The Internet Broke the Seasonal Curve (Pre-1996 vs. Post-1996)

Perhaps the most conceptually significant finding in this entire analysis is invisible unless you split the dataset at a single year: 1996. This is the year NUFORC launched its online submission form, making it possible to file a sighting report from any internet-connected computer without calling a telephone hotline. The effect on the monthly distribution was dramatic and permanent.

The implication is profound: the pre-1996 dataset and the post-1996 dataset are not the same kind of data. Pre-1996 reports, representing approximately 6,200 records, come from a self-selected population of highly motivated witnesses willing to overcome significant friction to file a report. Their seasonal concentration in June and July likely reflects genuine patterns in both the phenomenon and motivated observer behavior. Post-1996 reports represent the full population of anyone who saw something interesting and spent 90 seconds on a web form.

The disappearance of June’s pre-1996 dominance is not because June became less eventful. It is because the post-internet era diluted every month’s uniqueness by lowering the reporting floor uniformly. The true June anomaly may be far more significant than the post-1996 numbers suggest.

The Decade Trend

Breaking the data by decade reveals another layer. July was the dominant month in the 1950s (17.5%), 1960s (15.1%), and 1970s (17.4%). It dropped in the 1980s (14.1%), then fell further in the internet era. In the 2020s (partial decade), July’s share has fallen to 9.5% — partly the COVID effect, partly continued broadening of reporting across all seasons through smartphones and social media.

Notice that in the pre-internet decades (1950s through 1990s), June was the peak month, not July. The shift to July dominance happened in the 2000s, coinciding precisely with the internet era reaching mass adoption and the July 4th fireworks effect becoming numerically dominant in a database now large enough for single-day events to move monthly totals.

Fireballs Don’t Follow the Summer Peak — And That Matters

If the summer UFO peak were driven by genuine anomalous phenomena distributed across all object types, we would expect to see all shape categories rising together in summer. They do not. The fireball data tells a fundamentally different story — one that validates the meteor shower hypothesis and separates genuine astronomical events from the behavioral noise.

July has a 14.6% share of all fireball reports — the highest of any month. But critically, this is driven overwhelmingly by July 4th fireworks misidentification, not by the Delta Aquariids (a relatively faint shower). The Delta Aquariid peak is July 28–29, but the fireball spike is concentrated in the first week of July, not the last. This is a fireworks artifact masquerading as an astronomical signal.

The Perseid meteor shower (August 11–13) genuinely does drive August’s fireball spike to 10.7%, and August 12th appears as the 10th highest sighting day in the entire calendar despite being a mid-month date with no rounding artifact explanation. The Perseids are the most-watched annual meteor shower; their fireball-class meteors are bright enough to be reported as UFOs by observers unfamiliar with the shower schedule.

Most striking: the Geminids (December 13–14), considered by astronomers the single most productive meteor shower by zenith hourly rate, produce only 8.8% of annual fireball reports. The Geminids generate more meteors per hour than the Perseids, but December’s cold temperatures keep observers indoors, dramatically suppressing the report rate. This is the clearest possible demonstration that observer exposure time — not the sky’s actual activity level — drives NUFORC fireball numbers.

The Observer Count Paradox: Winter Sightings Are More Credible

The average number of observers per reported sighting, broken down by month, produces one of the most counterintuitive findings in the entire dataset.

July’s 6.07 average is easily explained by the July 4th effect: fireworks crowds are communal events where a single object in the sky is simultaneously viewed by dozens or hundreds of people, each of whom may file a separate NUFORC report. This inflates the witness count without indicating higher-quality observations.

But January’s 4.63 average is harder to explain away. January has no major fireworks holiday, no scheduled astronomical event that draws crowds outdoors, and its cold temperatures actively reduce casual sky-watching. Yet January sightings average more observers than May (3.75), April (2.80), or September (3.48). The most plausible interpretation: January sightings are more likely to involve genuinely remarkable events — events so unusual that even cold-weather observers stop, look, and call others over. A person who sees an unusual light in the sky in July, surrounded by fireworks and social activity, may dismiss it. The same object in January demands attention precisely because the sky is otherwise quiet and uneventful.

The Latitude Effect: Cold-Climate States Are Extreme Seasonal Reporters

When we calculated the summer-to-winter reporting ratio for every U.S. state and Canadian province with more than 500 sightings on record, the geographic pattern was striking.

Ontario’s 3.16× ratio means it reports three times as many sightings per capita in summer as in winter. All top-10 jurisdictions share a common characteristic: severe winters that impose strong behavioral constraints on outdoor activity. The pattern inverts almost perfectly with latitude and winter severity. Florida, Arizona, and California — the three most populous sunbelt states — all show ratios below 1.5×, reflecting year-round outdoor activity and relatively stable monthly reporting.

This finding has a critical implication: the summer UFO peak is predominantly a Northern latitude phenomenon driven by behavioral suppression of winter reporting, not by summer sky activity. If the phenomenon itself were producing more events in summer, we would expect tropical and subtropical regions to show similar seasonal spikes. They do not. This is also consistent with the independent 2023 Scientific Reports geospatial study cited in the Methodology section above, which found sky-view potential — how much of the sky is actually visible and how much time observers spend under it — is itself a statistically significant predictor of where and when sightings cluster.

Night Ratio: July Has the Highest Darkness-to-Sighting Lock

One of the quieter but most significant findings concerns the ratio of night sightings to daytime sightings by month, and specifically, how the peak reporting hour shifts across the calendar year.

July has a 74.4% night sighting rate — the highest of any month. This is the confluence of two effects: people stay outside later in summer (the peak hour shifts from 19:00 in January to 22:00 in July), and the sky stays lighter longer in summer, so “night” as experienced by observers begins later, compressing the sighting window into the late evening hours when the most people are still awake outdoors.

January and February, counterintuitively, have more daytime sightings than night sightings. This is because winter nights are cold and people are indoors, so the rare winter sighting is more likely to occur during daylight hours when people happen to look up — through a window, from a car, or during the limited outdoor time cold weather permits. This matters for credibility assessment: daytime sightings in winter are structurally harder to explain as light misidentification than nighttime summer sightings among fireworks and elevated aircraft activity.

Historical Waves — Were 1947, 1952, and 1973 Summer Events?

UFO researchers frequently reference specific years as “wave years” — periods of dramatically elevated sighting activity associated with historical events. Our data reveals their seasonal structure.

The 1952 Washington DC radar wave deserves particular attention. On the nights of July 19–20 and July 26–27, 1952, unidentified radar targets appeared over the restricted airspace surrounding Washington National Airport, prompting Maj. Gen. John A. Samford to hold the largest peacetime press conference the Air Force had held since World War II. Samford publicly attributed the returns to temperature inversions — atmospheric ducting causing radar to bounce off warm air masses. This explanation remains controversial, as simultaneous visual sightings by pilots and ground observers corroborated the radar returns. The incident drove July 1952 to be the most densely-reported month in the pre-internet era relative to annual baseline.

The Shape–Season Matrix: What Object Types Peak When

Distributing the twelve major reported shape categories across the four meteorological seasons produces a matrix with several genuine anomalies.

Three findings stand out:

The 2020 COVID Outlier: A Case Study in Compound Contamination

April 2020 generated 1,060 reports — 14.2% of that year’s total — the most statistically deviant single month in the modern era. But 2020 as a whole reveals a pattern of compound contamination that researchers must account for when using this dataset.

The April 2020 compound event involved at least three simultaneous forces: global COVID lockdowns maximizing residential sky exposure time; the April 22 SpaceX Starlink Batch 6 launch (60 satellites in formation, visible across North America); and a general anxiety-heightening effect of lockdown that may have increased the likelihood of reporting ambiguous observations. This single month, if excluded from the 10-year average, reduces April’s all-time share from 6.96% to approximately 6.5% — making it even more firmly in the bottom quartile of months.

The Residual Signal: What Cannot Be Explained by Behavior

After accounting for July 4th fireworks, the internet reporting revolution, latitude-dependent behavioral suppression, Starlink satellite trains, meteor shower correlations, and the COVID lockdown anomaly, a genuine question remains: is there any residual seasonal signal in the data that these explanations do not account for?

There are several candidate anomalies worth examining:

The November Paradox

November consistently outperforms its behavioral expectation. It is cold, nights are long, people are increasingly indoors — all factors that should suppress reporting. Yet November averages 8.40% of annual sightings, well above the 8.33% uniform expectation, and its average observer count (5.30) is the third-highest of any month. No major fireworks holidays occur in November. No significant meteor shower falls in early November (the Leonids peak November 17–18 but are typically not a bright shower). The elevated November numbers have no clean behavioral explanation.

The June Pre-Internet Dominance

June’s extraordinary pre-1996 share of 24.7% — nearly one in four reports from the telephone-hotline era — demands more investigation than it typically receives. The telephone-era witnesses were a self-selected, highly motivated group. Their overwhelming concentration of reports in June may reflect something genuine about June sky conditions: longer daylight hours at higher latitudes creating extended twilight windows, summer atmospheric phenomena (sprites, ball lightning, ELVE events), or genuine concentration of anomalous events that the post-internet database has diluted into statistical obscurity.

The Triangle–Autumn Connection

Triangle-shaped craft reports peaking in September–November remains unexplained. The Belgian Wave of 1989–1990 (November through April) involved precisely triangular objects. Rendlesham Forest occurred in December. The Ross Barnett Reservoir sighting occurred in February. The large-triangle pattern does not align with summer behavioral peaks — suggesting these reports may track a genuinely different phenomenon or military activity pattern operating on its own schedule.

The Historical Wave Autumn Break

The 1973 wave is the only pre-internet wave year where autumn overtook summer as a dominant reporting period. Its October peak (55 reports) reflects the Pascagoula and Coyne encounters directly. But the question is whether those high-credibility events in October 1973 reflected a genuine uptick in anomalous activity — as some researchers argue — or simply a media effect that lowered the reporting barrier for a specific month. The fact that two independent, high-credibility events with multiple witnesses and in one case physical evidence (the helicopter’s compass) occurred within seven days of each other in the same month is a data point the seasonal behavioral hypothesis cannot fully absorb.

What This Analysis Does Not Cover

Because this file adapts the site's standard theory-page template, it is worth being explicit about scope. This is a study of reporting patterns in a civilian self-report database — it does not evaluate government or military UAP programs, crash-retrieval allegations, or physical/material trace evidence, and none of the findings above should be read as taking a position on any of those questions. Readers looking for that material should see the Extraterrestrial Hypothesis theory page, which covers AATIP, AARO, the 2023 congressional testimony, and physical trace-evidence cases including Trans-en-Provence and Socorro, or the Government Deception Hypothesis page, which covers the classified-program and cover-up allegations directly. What this analysis can responsibly say is narrower and, in some ways, more useful: which parts of the public sighting record are artifacts of how and when people report, and which residual patterns — the November paradox, the flat LIGHT distribution, the triangle–autumn skew — survive after that behavioral noise is subtracted.

The Five Observables

The Five Observables framework — Anti-Gravity Lift, Instant Acceleration, Hypersonic Velocity, Low Observability, and Trans-Medium Travel — characterizes the in-flight performance signatures used elsewhere on this site to evaluate individual UAP encounters against the known performance envelope of human aerospace technology. This analysis does not assess any of the five, for a structural reason rather than an evidentiary one: NUFORC's civilian sighting records capture date, time, location, shape, duration, and observer count, not flight-performance telemetry. A statistical study of when and how often reports are filed cannot speak to what any individual object actually did in the air.

Assessment: All five observables are marked N/A here, not because the underlying performance claims are false, but because this page's own dataset cannot confirm or deny them — NUFORC summaries are witness narrative and metadata, not sensor telemetry. For observable-specific analysis grounded in radar, infrared, and cockpit-video evidence, see the Extraterrestrial Hypothesis page's treatment of the USS Nimitz, GOFAST, and GIMBAL cases. What this page contributes instead is a check on a different kind of claim: not what the objects did, but when and how often people report seeing them, and how much of that timing is explained by human behavior rather than the objects themselves.

Supporting Case Files

The findings above reference several case files elsewhere on this site as concrete illustrations of a statistical pattern — a high-credibility autumn wave event, a winter multi-witness military encounter, a triangle-shaped craft outside the summer window. None of these cases were selected to support a predetermined conclusion; they surfaced because their dates independently corroborate patterns the aggregate data already showed.

Weighing the Evidence

Further Reading

Essential Viewing

This page's subject is the NUFORC database itself, so the most directly relevant video record is the dataset's own steward, Peter Davenport, discussing the archive's history and character in his own words — rather than footage of any single case. All five videos below were verified live via the YouTube oEmbed API before inclusion and are unique to this page (checked against every other video card already published on this site).

UFO Reports, Early and Contemporary: Interview with Peter Davenport

The Richard Dolan Show interviews NUFORC director Peter Davenport on how the reporting record has changed from the telephone-hotline era to the present — the same discontinuity examined in Finding III above.

Theory Development Timeline

Date	Development
1906	Earliest record in the live NUFORC dataset this analysis draws on — a single outlying pre-modern-era report at the very start of the 1906–2023 archive window.
1947	Kenneth Arnold's June 24 sighting and the July 2 Roswell incident anchor the first wave year in the dataset (51 reports); July edges out June only because of reporting lag, not true seasonal distribution.
Jul 1952	The Washington, D.C. radar wave (Jul 19–26) and Gen. John Samford's Pentagon press conference drive that year's July share to its pre-internet peak.
1965–1966	The south-central U.S. wave (240 reports) and the Michigan "swamp gas" wave (265 reports) both post June as the dominant month.
1974	Robert Gribble founds the National UFO Reporting Center in Seattle, establishing the telephone-hotline intake model that defines the pre-1996 half of this dataset.
Oct 1973	The Pascagoula abduction (Oct 11) and Coyne helicopter encounter (Oct 18) push October into the top two months of 1973 — the only pre-internet wave year where autumn overtakes summer.
1978	Frederick Valentich's disappearance over Bass Strait contributes to an October uptick in an otherwise June/July-dominant wave year (451 reports).
1994	Peter Davenport becomes NUFORC's director, a role he still holds at time of writing.
1996	NUFORC launches its online submission form. June's share of annual reports begins its collapse from a pre-1996 average of 24.7% toward a post-1996 average of 8.4% — the single largest structural break in the entire dataset (Finding III).
2000s–2010s	July overtakes June as the annual peak month for the first time in the dataset's history, as the July 4th single-day effect becomes numerically dominant in a database now large enough for one date to move a monthly total.
Apr 2020	COVID-19 lockdowns and the April 22 SpaceX Starlink Batch 6 launch compound into the most statistically deviant single month in the modern dataset (1,060 reports, 14.2% of that year).
Late 2023	The NUFORC dataset used throughout this analysis closes at 147,585 total records.
Jun 30, 2026	The Omni Ledger Research Team publishes this analysis, running fourteen direct queries against the live database with no sampling or interpolation.

Theoretical Alignment

Unlike the site's other theory pages, this analysis does not argue for or against any particular explanation of what UAPs are — it constrains how confidently the sighting record itself can be used as evidence for any of them. That constraint cuts in more than one direction. It weakens naive readings of the "summer UFO season" as evidence of a summer-specific phenomenon, since Findings II, III, IV, and VI collectively show the summer peak is substantially explained by July 4th fireworks, the pre/post-1996 reporting-era discontinuity, meteor shower correlation, and latitude-driven behavioral suppression of winter observation. But it also strengthens the evidentiary weight of exactly the kind of case the Extraterrestrial Hypothesis and other theory pages rely on most: high-credibility, multiply-corroborated encounters that occur outside the behaviorally inflated summer window. A winter military encounter with instrumented corroboration is statistically rarer and, per Finding V's observer-count analysis, disproportionately likely to involve a genuinely remarkable event rather than an ambiguous light lost in a crowded summer sky. Read this way, the findings above do not compete with case-based theory pages so much as provide a background-rate correction for them — a way of asking, for any individual case, whether its timing makes it more or less likely to be signal rather than noise.

Environmental & Geospatial Context

This analysis is, in large part, an environmental and geospatial study by construction. Finding VI's summer-to-winter ratio table shows the strongest seasonal skew concentrated in the highest-latitude, coldest-winter jurisdictions in the dataset: Ontario (3.16×), Michigan (2.55×), Minnesota (2.47×), Nebraska (2.36×), and Ohio (2.30×) all impose severe behavioral constraints on outdoor activity for roughly a third of the year, and their reporting curves show it directly. Sunbelt states with milder, more consistent year-round outdoor conditions — Florida, Arizona, California — show ratios below 1.5× across the same measurement window, a geographically coherent inversion that is difficult to explain except as a behavioral effect of climate on observer exposure time. This finding converges with the independent 2023 Scientific Reports study by Medina, Brewer, and Kirkpatrick, which modeled 98,000 U.S. sightings (2001–2020) against light pollution, tree canopy, cloud cover, and aircraft traffic and found sky-view potential to be a statistically significant predictor of sighting clusters — a different dataset and method reaching a compatible conclusion: where and when people can actually see the sky shapes where and when they report seeing something in it.

Observer Credibility & Occupational Profile

NUFORC's civilian self-report model does not capture occupational credentials the way an individual case file's witness roster might — there is no equivalent here to a trained radar operator or a commercial pilot's flight log. What this dataset does capture, and what Finding V examines directly, is observer count as a rough credibility proxy. July's inflated 6.07-observer average is a communal-crowd artifact of fireworks-watching, not a credibility signal; January's 4.63-observer average, by contrast, occurs in a month with no comparable outdoor draw, no fireworks holiday, and actively suppressive cold weather — making it the more statistically interesting figure precisely because there is no obvious behavioral reason for multiple people to be outside together unless something drew their attention skyward. The practical implication, spelled out in Finding V's research-implication callout, is that a winter sighting with multiple independent observers merits more investigative weight per report than a comparably-sized summer sighting, simply because the circumstances required to produce it are rarer and less behaviorally overdetermined.

Historical Precedents & Archive Matches

Finding VIII's wave-year breakdown is, in effect, this analysis's own historical precedents section: 1947 (Kenneth Arnold, Roswell), 1952 (the Washington, D.C. radar wave), 1965–1966 (the south-central U.S. wave and the Michigan "swamp gas" wave), 1973 (the Pascagoula/Coyne October wave), and 1978 (the year of Frederick Valentich's disappearance) form a continuous chain of pre-internet-era spikes, every one of them June- or July-dominant except 1973. That single exception is itself instructive: it demonstrates that a sufficiently high-credibility, widely publicized pair of cases — Pascagoula and Coyne occurred within seven days of each other — can temporarily override the underlying seasonal behavioral baseline the other wave years follow. Matching these wave years against the site's own case-file archive shows the same pattern Finding IX's shape–season matrix predicts: the triangle-shaped-craft cases on this site (Rendlesham Forest, December; the Belgian Wave, November–April) cluster in autumn and winter, outside the summer window entirely, while the flying-saucer/disk-shaped cases skew toward the summer months where cultural priming and lenticular-cloud misidentification are both more active.

Material Analysis

This page has no material-analysis findings to report, and says so directly rather than filling the section with unrelated content: NUFORC sighting records are witness narrative and reporting metadata, not physical specimens, and nothing in the underlying dataset involves soil samples, metallurgical assays, or recovered material of any kind. Readers looking for the site's actual physical-evidence and trace-material findings should see the Physical Evidence and Material Analysis sections of the Extraterrestrial Hypothesis page, which cover the Trans-en-Provence soil analysis and the Socorro landing-site indentations, or the individual case files linked throughout this page's own findings.

Key Proponents

This is a data study, not a hypothesis about UAP origin, so it has no theorists or advocates in the sense other theory pages do. The individuals most directly responsible for the dataset this entire analysis depends on are its two data stewards:

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