Within Pattern Illusion
Who Actually Counts as a Mysterious Researcher?
A death cluster can grow dramatically when scientists, support staff, contractors and institutional associates are treated as one research group.
On this page
- How occupational categories expand after a story begins
- The difference between scientific work and institutional proximity
- Why membership criteria must be fixed before counting cases
Page outline Jump by section
Introduction
Suspicious-death narratives can become much larger without adding a single new death. The expansion happens when the definition of “scientist” quietly changes. A list may begin with researchers doing specialised aerospace, defence or propulsion work, then absorb engineers, technicians, contractors, former employees, administrators and people whose main connection is simply employment at the same laboratory or institution. The resulting population sounds coherent — “scientists connected to sensitive research” — while containing people with very different occupations and access.
That matters because a death cluster cannot be meaningfully assessed unless there is a reasonably stable answer to who belongs in the population being counted. Official occupational systems distinguish scientific and engineering work from administrative and other jobs, while cluster-investigation guidance stresses explicit inclusion criteria.[Office for National Statistics]ons.gov.ukOffice for National StatisticsSOC 2020 - Office for National StatisticsMay 5, 2026… In alleged UFO, antigravity and sensitive-technology death clusters, therefore, the label attached to each person is not a minor semantic issue. It can determine whether an apparent pattern exists at all.
How the category grows after the story begins
“Scientist” has an everyday meaning loose enough to conceal several different populations. A physicist conducting experiments, an engineer designing guidance systems and a technician supporting laboratory equipment may all plausibly be described as technical personnel. But that does not make them members of the same occupational population, much less participants in the same research programme.
Formal classifications make these distinctions because they matter statistically. The UK Office for National Statistics classifies jobs according to their work and skill content. Its Standard Occupational Classification places science, research, engineering and technology professionals in one major occupational group while administrative occupations form another. Within the professional group it separately identifies natural and social scientists, engineers and information-technology professionals.[Office for National Statistics]ons.gov.ukOffice for National StatisticsSOC 2020 - Office for National StatisticsMay 5, 2026… The US Bureau of Labor Statistics similarly describes life, physical and social science occupations as jobs in which workers use scientific research to solve problems and expand knowledge.[Bureau of Labor Statistics]bls.govBureau of Labor StatisticsLife, Physical, and Social Science Occupations: Occupational Outlook Handbook:: U.S. Bureau of Labor Statisti…
Even broad official definitions are normally explicit about their breadth. The US National Center for Science and Engineering Statistics notes that there is no single definition of the science-and-engineering workforce, so its analyses specify whether membership is being determined by occupation, degree or use of technical expertise. Its occupational definition covers computer and mathematical scientists, life scientists, physical scientists, social scientists and engineers; it separately recognises “S&E-related” occupations requiring technical expertise.[NCSES]ncses.nsf.govScience and Engineering Labor Force | NCSES | NSFSeptember 26, 2019…
That qualification is crucial. Broad categories are not inherently illegitimate; unstated and changing categories are. A researcher could reasonably study “scientists and engineers”, “all STEM workers” or “every employee of a particular defence laboratory”. Those are different populations, however. The denominator — everyone who could have become a case — changes every time the definition changes.
In a suspicious-death narrative, expansion can work in one direction. A physicist with an unusual research interest obviously qualifies. A systems engineer is admitted because engineering is technically adjacent. A software specialist is included because advanced projects depend on computing. A contractor is included because the contractor worked at the same facility. An administrator is included because the facility handles classified work. A former employee is included because of past access. Eventually, institutional association itself functions as the criterion, even though the group continues to be described publicly as “scientists”.
The number of apparently related cases has increased, but so has the underlying population from which cases can be selected. Without acknowledging that second change, the larger case count can create a misleading impression of increasing statistical significance.
A current case shows the difference between occupation and proximity
Melissa Casias provides an unusually clear example because her occupational status is documented rather than speculative. Casias disappeared in New Mexico in June 2025 and her remains were identified after being found in Carson National Forest in May 2026. She worked at Los Alamos National Laboratory, an institution whose nuclear-weapons mission makes any unexplained disappearance potentially attractive to sensitive-research narratives. But reporting by CBS identified her job as administrative assistant, not scientist.[CBS News]cbsnews.comCBS NewsLab worker who vanished last year found dead in New Mexico national forest - CBS NewsJune 1, 2026…
That distinction was also emphasised before her remains were found. Reporting on the wider group of deaths and disappearances quoted Casias’s niece, Jazmin McMillen, saying that Casias was an administrative assistant, did not have high-level clearance and that she had seen no evidence connecting her disappearance with the other cases.[WGHN]wghn.comwhat we know about deaths disappearances of staff at government labswhat we know about deaths disappearances of staff at government labs Other reporting cited a private investigator working for family members who said Casias handled office-supply purchasing and that the family rejected suggestions that she had sensitive scientific involvement.[The US Sun]the-sun.comDespite public speculation tying Casias’s case to a series of missing or deceased individuals connected with sensitive U.S. government or…
Yet the institutional connection was powerful enough for Casias to become part of a broader “scientists” story. CBS itself more carefully described the emerging set as missing or deceased “scientists and laboratory staff”, a phrase that preserves an important distinction erased when the entire group is shortened to “scientists”.[CBS News]cbsnews.comCBS NewsLab worker who vanished last year found dead in New Mexico national forest - CBS NewsJune 1, 2026… Later coverage similarly called her a laboratory employee or administrative assistant while discussing her alongside scientists and other staff associated with government facilities.[Los Angeles Times]latimes.comOpen source on latimes.com.
The Casias case does not establish that her death was ordinary, nor does her administrative job settle what happened to her. At the time of the cited reporting, important questions about the circumstances remained under investigation. The narrower point is methodological: whatever happened to Casias, employment at Los Alamos did not make her a scientist. Treating those as interchangeable claims changes the composition of the supposed research cluster before any causal evidence has been considered.
The slippage can go further. A specialist UFO-oriented case page correctly identifies Casias as an administrative assistant but then speculates that administrative personnel with high clearance may handle classified material.[UFOUAP]ufouap.commelissa casiasmelissa casias That illustrates how occupational distance can be overcome narratively: once scientific work is no longer necessary for inclusion, presumed access to people, documents or facilities can perform the same role. The proposition has changed from “researchers working on a common subject are disappearing” to the much broader “people who might have been near sensitive information are disappearing”.
Those propositions require different evidence and different comparison populations.
The Marconi story shows how a label can outgrow one employer
The historical GEC-Marconi deaths provide another useful example because the category was already contested while the events were occurring. Contemporary reporting in April 1987 focused initially on a striking, comparatively narrow observation: several people associated with Marconi and sensitive defence work had died in unusual circumstances. The Los Angeles Times, for example, described David Sands as the third scientist working for Marconi to die in violent circumstances within six months and noted another scientist engaged in similar work who had disappeared.[Los Angeles Times]latimes.comOpen source on latimes.com.
Parliamentary records confirm that particular deaths generated genuine questions. In April 1987, an MP asked the Home Secretary about police investigations into the 1986 deaths of Vimal Dajibhai and Arshad Sharif. The government replied that the investigations had been completed, with an open verdict recorded for Dajibhai and suicide for Sharif.[UK Parliament API]api.parliament.ukscientists deathsscientists deaths In March 1988 another parliamentary question grouped six named men — Victor Moore, Sharif, Dajibhai, Sands, Peter Peapell and John Brittan — and asked about security implications, Marconi subcontracting and a Ministry of Defence police investigation. The government answered no to the questions posed.[UK Parliament API]api.parliament.ukscientists deathsscientists deaths
What matters here is not whether every contemporary official conclusion was correct. It is how the population subsequently became less precise. Later versions of the “Marconi scientists” list have incorporated not only Marconi scientists but engineers, software specialists, Ministry of Defence personnel, employees of other defence companies, academics, technicians and people connected through increasingly indirect institutional relationships. Contemporary parliamentary questions themselves show that even the relatively early set already required questions about whether particular individuals had actually done subcontracting work for Marconi.[UK Parliament API]api.parliament.ukscientists deathsscientists deaths
The label can become still broader when this historical defence-industry story is retrospectively incorporated into UFO narratives. Current online discussions sometimes describe the deaths as involving people connected with “UFO type research”, while other participants point out that the original association was principally with defence and Strategic Defense Initiative work rather than demonstrated UFO research.[Reddit]reddit.comOpen source on reddit.com. Reddit is not evidence for the underlying deaths, but it is useful evidence of how the story is now being categorised and disputed.
This creates several nested populations that should not be silently merged:
- people who personally conducted UFO or unconventional-propulsion research;
- scientists or engineers working on Strategic Defense Initiative or other advanced defence programmes;
- technical employees of Marconi or related defence companies;
- contractors or government personnel associated with those organisations;
- employees of relevant laboratories regardless of occupation;
- people whose connection is primarily institutional, professional or social.
Each enlargement makes it easier to find another death that can be described as connected. None by itself demonstrates that the new case shares the cause hypothesised for the original cases.
Scientific work is not the same as institutional proximity
Large laboratories and defence organisations are especially vulnerable to this confusion because scientific institutions employ many people who are not scientists. Research organisations require finance, procurement, security, computing, administration, maintenance, facilities management and other support functions. The UK Department for Education explicitly notes that science and technology industries require a wide range of occupations, including administrative ones, even when analysing the supply of skills for science and technology.[Explore Education Statistics]explore-education-statistics.service.gov.ukOpen source on service.gov.uk.
The distinction can be expressed as three different kinds of connection.
Occupational connection means the person actually performed scientific, engineering or closely defined technical work. Research connection means there is evidence that the person’s work concerned the specific technology or programme under discussion. Institutional connection means the person worked for, contracted with or was otherwise associated with an organisation that also conducted such research.
These connections are not equivalent. A scientist at Los Alamos can have a scientific occupational connection without working on the particular programme relevant to a theory. An administrator can have a strong institutional connection without conducting research at all. A contractor might perform technically sophisticated work without having access to the project that supposedly motivated an attack.
Security clearance introduces another potential substitution. Clearance or access can be independently relevant if the hypothesis concerns classified information rather than scientific discovery. But if that is the hypothesis, the population must be defined accordingly — for example, “people with documented access to programme X” — rather than continuing to call them scientists. Otherwise occupational prestige and institutional secrecy are doing rhetorical work that the evidence has not established.
This is particularly important for UFO and alleged antigravity narratives because the proposed research boundary is already unusually elastic. Aerospace engineering, nuclear weapons, advanced propulsion, space science and classified defence research can all sound adjacent to UFO technology without evidence that a particular person’s actual work concerned UFOs or unconventional gravity. Once mere employment at an institution active in one of those fields is sufficient, the pool of possible cases becomes very large.
Why the membership rule has to come before the deaths
Public-health cluster investigation offers a useful methodological analogy without implying that suspicious deaths are epidemiological events. The US Centers for Disease Control and Prevention explains that a cluster case definition sets specific criteria for deciding who is included and helps investigators estimate and assess a cluster’s size. Earlier CDC guidance similarly distinguishes narrow from expanded case definitions: broadening a definition naturally captures more cases, but the additional cases should still have a defensible relationship to the suspected common cause.[CDC Stacks]stacks.cdc.govStacks Cluster Detection and Response Guidance for Health DepartmentsStacks Cluster Detection and Response Guidance for Health Departments
That principle exposes the problem with retroactively assembled death lists. Suppose the initial hypothesis is that researchers studying unconventional propulsion face an unusual risk. If no convincing excess appears, expanding membership to all aerospace engineers changes the question. Adding defence contractors changes it again. Adding everyone employed at nuclear or aerospace laboratories changes it much more dramatically.
The appropriate test is therefore not simply, “Can a connection to sensitive research be found?” For organisations as large and interconnected as national laboratories, universities, defence companies and government agencies, some connection will often be available. A more discriminating assessment asks:
- What qualified a person for the group before their death was considered? Job title, actual research, named project participation, clearance, employer or something else should be specified.
- Would the same rule include living colleagues? If a rule identifies dead people readily but nobody has attempted to enumerate the much larger living comparison population, a death rate cannot be inferred from the list.
- Is the rule applied symmetrically? A technician should not become a “scientist” only when the technician dies, while comparable living technicians disappear from the denominator.
- Has the definition changed as new cases appeared? If “UFO researcher” becomes “advanced-technology scientist”, then “defence engineer”, then “government-lab employee”, increases in the case count partly reflect category expansion.
- Does each person’s alleged sensitive connection have independent documentation? Employer reputation is not a substitute for evidence about the individual’s actual duties.
The need for a denominator is particularly important. Research on cluster detection shows how selection problems can inflate false-positive findings when the observed sample does not properly represent the underlying population.[PubMed Central (PMC)]pmc.ncbi.nlm.nih.govOpen source on nih.gov. The exact statistical techniques used in disease studies are not directly transferable to alleged assassination clusters, but the underlying lesson is: selecting conspicuous cases without a well-characterised population at risk makes an apparent excess difficult to interpret.
A tighter label can make the mystery smaller — and more testable
None of this proves that every death or disappearance attached to UFO, antigravity or sensitive aerospace research is unrelated. Narrowing the population does the opposite of dismissing the hypothesis: it makes a genuine connection easier to test.
If several people can be shown to have worked directly on the same unconventional-propulsion programme, possessed the same unusually restricted information and then experienced statistically or forensically similar events, that is a substantially stronger proposition than observing that several deceased people once worked somewhere in the enormous aerospace, defence or nuclear ecosystem. A narrow definition may produce fewer cases, but those cases carry more evidential weight.
The current Casias example makes the distinction unusually visible. Her employment at Los Alamos is real; her disappearance and death are real; the wider investigation and speculation are real. But reliable reporting identifies her as an administrative assistant, and a family member explicitly disputed both high-level clearance and evidence connecting her with the other cases.[CBS News]cbsnews.comCBS NewsLab worker who vanished last year found dead in New Mexico national forest - CBS NewsJune 1, 2026… Calling her a “scientist” therefore adds apparent occupational similarity that the available evidence does not support.
The older Marconi narrative presents the same problem on a larger historical canvas. There were genuine deaths, genuine defence connections and genuine parliamentary questions.[UK Parliament API]api.parliament.ukscientists deathsscientists deaths What cannot simply be assumed is that everyone subsequently attached to the story belonged to one scientific research population, still less one UFO or antigravity programme.
That is why the apparently simple question “Who counts as a mysterious researcher?” is central rather than pedantic. Before counting suspicious deaths, the category has to stop moving. Otherwise every new occupational or institutional association can enlarge the numerator while the unseen comparison population expands without being counted — producing a more dramatic list without necessarily producing stronger evidence of a common cause.
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Endnotes
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Additional References
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US adversaries may have taken out [missing scientists]({{ 'missing-scientist/' | relative_url }}): Eric Burlison | Elizabeth Vargas Reports...
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12 U.S. Scientists Have Gone Missing or Died. What's Going On?...
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California scientists among 10 dead or disappeared...
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