The Ethical Skeptic

Challenging Pseudo-Skepticism, Institutional Propaganda and Cultivated Ignorance

A Statistical Profiling of Celebrity Wannabe ‘Scientific Skeptics’

Yeah yeah… We know, you are a skeptic. Yawn. But what else have you done, aside from foist your name inside a list of dead scientists, among whom you would otherwise never merit inclusion? Is your ego that fragile and desperate? A sweep through some analytics regarding social skeptics reveals some startling, yet not totally unexpected results. Psychologists who have inchoate activated the fragile and angry – a thunder chamber of sycophants dictating to everyone else what we all should think.

Remember the old game show called Hollywood Squares? The tic-tac-toe styled game set after which the show was themed, was staffed by a rotating/regular cast of celebrities who would answer questions on behalf of the game show participants. These celebrities were people who were supposedly famous, but for the life of us, no one back then who watched the show could recall why they were famous. These celebrities were famous simply for being famous. I always suspected that some of the ‘celebrity’ participants were in fact no-name citizens who had been inserted into the group of actually famous people, and were presumed to be themselves famous from then on.

Well that model bears curious utility inside the skeptic movement. Skeptics today stand upon a perch of celebrity that is derived simply from pretending to be skeptics in the first place – and a habit of promoting themselves opportunistically inside rosters of names which include personages of true brilliance, accomplishment and renown. However unlike Hollywood Squares, many of those personages are now deceased, fully unable to object over such abuse of their legacies.

Wikipedia maintains a suitably comprehensive listing of America’s most noteworthy (notorious) social skeptics (Wikipedia: List of scientific skeptics).1 Given the reality that Wikipedia allows social skeptics to run amok inside the bowels of its editing and practices of dissenting editor abuse, I feel fairly confident that all the acceptable Who’s-Who of social skepticism are therefore listed therein. Skeptics who are not listed in this tally have committed a misstep in some regard, as viewed by the Cabal – violated the Ministry of Truth’s policy on compliance in some way which has prompted their exclusion from the club. They have failed in their mandatory Schapiro Utterances. With the exception of those who earned their notoriety by actually accomplishing something of merit in their careers, something besides just declaring themselves to be a skeptic, I think we have the right listing inside the Wikipedia lineup (see footnote 1 above).

Were I a prominent physicist or mathematician, I would not want to be included within this group.

This is a cache of persons so desperate to get their names inscribed into a science hall of fame, alongside the likes of Brian Cox, Stephen Jay Gould, and Richard Feynman, that they would literally do and say anything, attack anyone, and push any form of half baked science – sell their very integrity – in order to be counted among such company. I never really completely grasped what was occurring in the minds of these poseurs, until this last decade of philosophical study. After decades of watching social skeptics and how they behave, I have come to the conclusion: It is all about the celebrity. Not one issue of advocacy entails an actual improvement in the lot of mankind. Feckless meaningless targets foisted to provide a theater stage, upon which they can show their wares – that seething miasma of the wont to be the smartest person in the room. They bear such a need to be right – that they must be identified with science, even if it costs every friend or ounce of self-respect they can bear forfeit.

No. It’s not by arguing with “kindness & care” that you break academic mafias, criminal organizations,
impostors (psychologists) & lobbying groups. It is by exposing them, making their lives miserable & targeting their audience. ~Nassim Taleb

So I thought I would take a quick walk through some of the statistics with regard to the profiles these pretenders have published on Wikipedia, just to see if some of my experience-based, yet nonetheless preconceived notions about the makeup of American skeptics, panned out. I was not disappointed. It was actually worse than I had thought.

Seven Inferential Breakouts Concerning Celebrity Wannabe ‘Scientific’ Skeptics

Light Representation of Relevant Degrees or Fields of Study

I am not sure whether to laugh or cry when I examine this first listing. Of the 81 celebrity wannabe and deceased skeptics inside the Wikipedia lineup, the largest contingent by far is represented by those who possess no degree, and have never served in any actual function which involves science, in their entire lives. The second largest, and first real professional group comprises psychologists, behavioral scientists and psychiatrists. This is followed by (refreshingly) physicists, philosophers and medical skeptics, tailed finally by a scant smattering of other science discipline representations.

That is a rather precipitous drop-off after ‘psychology’ and ‘none’. Should not this familiar Pareto bias concern those in the Cabal, at least a little?

Not simply over the matter of lack of qualification, but moreover concerning the propensity for establishing conclusion through the ease of ad hoc and pseudo-theory claims based upon the notion, ‘your mind created this’. A non-testable conclusion which explains everything, anything and nothing, all at the same time. A cadre of psychologists and magicians do not make for good investigators – as they both are experts in abductive inference – which is weak in its bootstrap, methodical and probative strengths.2

What one should note with grave concern, is that those professional groups in red, those who conduct real Karl Popper science based upon authentic disciplines of deduction, probative study and hypothesis, these compose a mere 15 individuals among the 81 skeptics listed. Of even more importance, half (7) of those individuals are also dead! A single engineer and a single mathematician? – yet 35 people who have not set foot in a university or a lab? C’mon guys, you have to do better than this. Does the idea even ever cross your mind to apply skepticism to yourselves?

Notoriety Attained through Invalid Thunder Chamber Promotion

Exhibit 1 to the right, demonstrates the breakout of the celebrity wannabe skeptic lineup in terms of how they attained their current notoriety. 11% of the listed members were inserted into the tally because they actually did something with their lives, of noteworthy accomplishment besides being a skeptic. Only 11%. Let that sink in, and you begin to understand inside this first graph that this is a peer pressure club. A club which foisted its approved names upon an important Wikipedia page, and then inserted the likes of Carl Sagan and Isaac Asimov, without their permission, in order to assuage their enormous egos. Of this thin margin 11% however, many of the accomplished scientists who employed skepticism as a part of science (how it is supposed to be employed), are now deceased – no longer able to stand up and say ‘No, this is not what I meant by being a skeptic. We were not trying to establish another religion, nor another persecutor of science.’

The notoriety of the skeptics who have inserted themselves into this charade in reality stems merely from active promotion by their club. This club of pretenders composes 86% of the entire listing. The lineup actually includes 70 out of 81 persons who belong to science enthusiast activist congregations like The Skeptics Society, Center for Inquiry or Skeptics in the Pub. An abysmal set of surreptitious contrivances – the epitome of not simply echo chamber, rather of appeal to authority thunder chamber.

Thunder Chamber – an appeal to authority version of echo chamber, much more imperious in its insistence and intimidating in its effect. A club of science communicators – catalyseurs seeking conflict between laypersons and scientists, to enable furtherment of their power as a furtive liaison therein.

This is how they obtained the visibility implied by the Wikipedia lineup – through club authority and intimidation.  It is transparently unethical.

Little Relevant Qualification or History of Professional Accountability

Exhibit 2 outlines the portion of the members listed in the tally, who actually attained a degree or have done work inside a discipline which might even be considered as science. A mere 57% of this group of skeptics maintain a career or background which would allow them to be trained in skepticism or the scientific method in the first place.

43% of this group bears no scientific qualification other than ‘self-identified skeptic’. If you remove the deceased scientists from the qualified group, this number of non-science trained ‘scientific skeptics’ jumps to 49% of the living total roster of ‘science skeptics’. Half of those determining the scientific skeptic worldview, the most vocal half – bear no scientific credential whatsoever.

A full 35 members or 43% of the list (both living and deceased), as you can see in the ‘Relevant Field or Degree’ graphic above right, possess no degree, background nor experience in any professional or social task which would serve to hold them accountable as to their ability to apply skepticism or science. This ‘being held accountable’ in a professional context is a critical qualification when one is evaluating their candidate celebrity skeptic. People who have performed in a career wherein they are regularly held to accountability (skin in the game), tend to act in completely different fashion from people who began their career as performers or celebrities, or have rarely ever had to produce anything other than ‘critiques’ of others. In a social context, one can get away with pretty much anything; much like in high school. Perhaps then it is no coincidence that high school style bullying often becomes a praxis, best method and club milieu of science skeptics.

Hold no Peer Accountability and Tend to Think Like a Stage Performer

Eighteen members of the Exhibit 3 group, or 22% of the entire tally, were stage or even professional magicians or illusionists. Another 21 were podcast hosts or convention organizers. People who get a charge out of manipulative influence tend to nurture a deception game running as a background theme – as this is their life blood. Even if their primary act is to put on a display of magic – under the context of ‘this is an illusion’; make no mistake, a magician craves the heady rush of a deception – and this foible does not end at the stage exit. The more deep and pervasive the fake, the more satisfying the ploy. I am a fan of the ‘It takes one to know one’ method of expertise validation; however all such deliberations are executed inside the context of complete transparency/accountability. In skeptic clubs, and in situations where only unaccountable critique is exercised, these individuals can claim no such congruence with an ‘it takes one to know one’ ethic.  Yes, ‘It Takes a Thief’ – but we do not then appoint that thief, chief of police nor head of the FBI. Heck, even those roles stand under accountability as to their performance. Skeptics are never held to account.

An epistemic commitment to exposing fraud, when executed under the desire to profit, ridicule and sway public opinion by means of publicity stunts, comes commensurate with a bias for self-aggrandizement and hyperbole. Attracting attention to self is not the same thing as marketing, and plays a key role in all such pathologizing of the supposed credulous and woo believer.

It is not a coincidence that nearly half of the celebrity wannabe skeptics in the analysis turned out also to be stage magicians and podcast hosts. This summation did not include those who merely attended or presented at skeptic media events. Take this as a curious warning. The ability to unaccountably control what large numbers of people perceive and believe, is an intoxicating and addictive opiate indeed. If your primary goal is to derive money/attention from such activity, you may make no claim to scientific or skeptical elevation over those you mock or deride.

Are Getting Old as a Group: Either Deceased or Average of 61 Years Age

21% of our tally of famous and wannabe famous skeptics are already dead – as is shown by Exhibit 4 to the right. The rest of the group of 64 are inching closer to their own Kuhn-Planck Paradigm shift event each year. Tick-tock, tick-tock. There are very few individuals in the tally, four to be exact, who are below the age of 35. Of those who are young in the tally few are individuals whom, without enormous social backing, would be desirous to carry forward the torch of the 1972 Skeptic’s Handbook. There are no new Michael Shermer’s and Carl Sagan’s budding within this group of attention-seekers. Most skeptics in the younger group tend to be angry, punk and Goth accentuated podcast hosts – devoid of any qualification; being more concerned about who it is they hate than any particular cause of suffering and enlightenment on the part of mankind.  In my best estimate, zero of these four people will continue inside the formal skeptical movement after the current Cabal dies off.

This does not bode well for social skepticism. Sixteen years left, for your critical thinking fantasy to play out. Each year you can feel your Cabal’s control on the mind of the American public slipping away from your pretend science, corporate apologizing and ignorance cultivating hands.

Few Have Been Involved in Any Actual Science

81% of the list is composed of poseurs who are called in ethical skepticism, Jamais l’a Fait. They have never done science- never been held to account regarding their dispensation of poorly crafted skepticism. This was supposed to be a ‘list of scientific skeptics’ – yet the vast majority of those in the list are not professionally skilled in such a task at all.

Jamais l’a Fait – Never been there. Never done that. Someone pretending to the role of designer, manager or policy maker – when in fact they have never actually done the thing they are pretending to legislate, decide upon or design.. A skeptic who teaches skepticism, but has never made a scientific discovery, nor produced an original thought for them self. Interest rate policy bureaucrats who have never themselves borrowed money to start a business nor been involved in anything but banks and policymaking. User manuals done by third parties, tax laws crafted by people who disfavor people unlike themselves more heavily, hotel rooms designed by people who do not travel much, cars designed by people who have never used bluetooth or a mobile device, etc.

Exhibit 5 shows this most distressing statistic in the entire analytical results set. Inside social skepticism, few of the living members have actually done any real science.

Too Heavily Represented by Psychology and Soft Sciences

Finally, Exhibit 6 shows that the majority (67%) of those in the more valid professional subset of the Wikipedia skeptic lineup, work inside the softer sciences of psychology, medicine and philosophy. If however, you add to this soft science group, those 35 individuals who bear absolutely no science experience whatsoever, you end up with 82% of the entire tally representing persons lacking in deductive and objective scientific experience.

Psychologists who have inchoate activated angry promotion-minded sycophants – bent on telling everyone what to think, under the guise of ‘critical thinking’.

Psychology functions off of inductive and subjective inference and evidence sets. It is not that these disciplines are unimportant or inappropriate, rather simply that – if a group is going to foist a claim to scientific and technological prowess – especially claims of absence, or conclusion that all observations are MiHoDeAL (Misidentifications, Hoaxes, Delusions, Anecdote and Lies) in nature – exorcised inside a context of supposed hard nosed epistemology – deduction and objective science. Then perhaps they should select a membership which is more representative of disciplines which function upon those value sets.

All this cast of Cabal characters is going to do, is to foment conflict between the public and science.
After all, this is what serves to both obscure them from being held accountable,
and as well serves to legitimize their methods and purpose in the eyes of a duped science and lay public.

Inside ethical skepticism, we believe that the appropriate discipline skills, as well as depth of experience, need be brought to bear inside any claim to represent science or the philosophy of science, skepticism. When you excise the legitimate 11% of this Wikipedia celebrity tally, those who actually made a difference in the world before they were ever considered skeptics, the remaining 89% compose a pitiful Cabal, a cast of characters which falls substantially short of what humanity demands from such an important social-scientific entity.

Skeptics, we demand better. You have 16 years left in which to ply your fake wares. You need to up your game.

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The Plural of Anecdote is Data

A single observation does not necessarily constitute an instance of the pejorative descriptive ‘anecdote’. Not only do anecdotes constitute data, but one anecdote can serve to falsify the null hypothesis and settle a scientific question in short order. Such is the power of a single observation. Such is the power of wielding skillfully, scientific inference. Fake skeptics seek to emasculate the power of the falsifying observation, at all costs.

It is incumbent upon the ethical skeptic, those of us who are researchers if you will – those who venerate science both as an objective set of methods as well as their underlying philosophy – incumbent that we understand the nature of anecdote and how the tool is correctly applied inside scientific inference. Anecdotes are not ‘Woo’, as most fake skeptics will imply through a couple of notorious memorized one-liners. Never mind what they say, nor might claim as straw man of their intent, and watch instead how they apply their supposed wisdom. You will observe such abuse of the concept to be most often the case. We must insist upon the theist and nihilist religious community of deniers, that inside the context of falsification/deduction in particular, a single observation does not constitute an instance of ‘anecdote’ (in the pejorative). Not only do anecdotes constitute data, but one anecdote can serve to falsify the Null (or even null hypothesis) and settle the question in short order. Such is the power of a single observation.

See ‘Anecdote’ – The Cry of the Pseudo-Skeptic

To an ethical skeptic, inductive anecdotes may prove to be informative in nature if one gives structure to and catalogs them over time. Anecdotes which are falsifying/deductive in nature are not only immediately informative, but moreover they are even more importantly, probative. Probative with respect to the null. I call the inferential mode modus absens the ‘null’ because usually in non-Bayesian styled deliberation, the null hypothesis, the notion that something is absent, is not actually a hypothesis at all. Rather, this species of idea constitutes simply a placeholder – the idea that something is not, until proved to be. And while this is a good common sense structure for the resolution of a casual argument, it does not mean that one should therefore believe or accept the null, as merely outcome of this artifice in common sense. In a way, deflecting observations by calling them ‘anecdote’ is a method of believing the null, and not in actuality conducting science nor critical thinking. However, this is the reality we face with unethical skeptics today. The tyranny of the religious default Null.

The least scientific thing a person can do, is to believe the null hypothesis.

Wolfinger’s Misquote

/philosophy : skepticism : pseudoscience : apothegm/ : you may have heard the phrase ‘the plural of anecdote is not data’. It turns out that this is a misquote. The original aphorism, by the political scientist Ray Wolfinger, was just the opposite: ‘The plural of anecdote is data’. The only thing worse than the surrendered value (as opposed to collected value, in science) of an anecdote is the incurred bias of ignoring anecdotes altogether. This is a method of pseudoscience.

Our opponents elevate the scientific status of a typical placeholder Null (such-and-such does not exist) and pretend that the idea, 1. actually possesses a scientific definition and 2. bears consensus acceptance among scientists. These constitute their first of many magician’s tricks, that those who do not understand the context of inference fall-for, over and over. Even scientists will fall for this ole’ one-two, so it is understandable as to why journalists and science communicators will as well. But anecdotes are science, when gathered under the disciplined structure of Observation (the first step of the scientific method). Below we differentiate four contexts of the single observation, in the sense of both two inductive and two deductive inference contexts, only one of which fits the semantics regarding ‘anecdote’ which is exploited by fake skeptics.

Inductive Anecdote

Inductive inference is the context wherein a supporting case or story can be purely anecdotal (The plural of anecdote is not data). This apothegm is not a logical truth, as it could apply to certain cases of induction, however does not apply universally.

Null:  Dimmer switches do not cause house fires to any greater degree than do normal On/Off flip switches.

Inference Context 1 – Inductive Data Anecdote:  My neighbor had dimmer switched lights and they caused a fire in his house.

Inference Context 2 – Mere Anecdote (Appeal to Ignorance):  My neighbor had dimmer switched lights and they never had a fire in their house.

Hence we have Wolfinger’s Inductive Paradox.

Wolfinger’s Inductive Paradox

/philosophy : science : data collection : agency/ : an ‘anecdote’ to the modus praesens (observation or case which supports an objective presence of a state or object) constitutes data, while an anecdote to the modus absens (observation supporting an appeal to ignorance claim that a state or object does not exist) is merely an anecdote. One’s refusal to collect or document the former, does not constitute skepticism. Relates to Hempel’s Paradox.

Finally, we have the instance wherein we step out of inductive inference, and into the stronger probative nature of deduction and falsification. In this context an anecdote is almost always probative. As in the case of Wolfinger’s Inductive Paradox above, one’s refusal to collect or document such data, does not constitute skepticism.

Deductive or Falsifying Anecdote

Deductive inference leading to also, falsification (The plural of anecdote is data). Even the singular of anecdote is data under the right condition of inference.

Null:  There is no such thing as a dimmer switch.

Inference Context 3 – Deductive Anecdote:  I saw a dimmer switch in the hardware store and took a picture of it.

Inference Context 4 – Falsifying Anecdote:  An electrician came and installed a dimmer switch into my house.

For example, what is occurring when one accepts materialism as an a priori truth pertains to those who insert that religious agency between steps 2 and 3 above. They contend that dimmer switches do not exist, so therefore any photo of one necessarily has to be false. And of course, at any given time, there is only one photo of one at all (all previous photos were dismissed earlier in similar exercises). Furthermore they then forbid any professional electrician from installing any dimmer switches (or they will be subject to losing their license). In this way – dimmer switches can never ‘exist’ and deniers endlessly can proclaim to non-electricians ‘you bear the burden of proof’ (see Proof Gaming). From then on, deeming all occurrences of step 2 to constitute lone cases of ‘anecdote’, while failing to distinguish between inductive and deductive contexts therein.

Our allies and co-observers as ethical skeptics need bear the knowledge of philosophy of science (skepticism) sufficient to stand up and and say, “No – this is wrong. What you are doing is pseudoscience”.

Hence, one of my reasons for creating The Map of Inference.

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Torfuscation – Gaming Study Design to Effect an Outcome

As important as is the mode of inference one employs commensurate with study completion, is the design of the study itself. Before one begins to attempt to reduce and analyze a body of observational resource, the ethical scientist must first select the study type and design that will afford them the greatest draw in terms of probative potential. The intricacies of this process present the poseur an opportunity to game outcomes of science through study design, type and PICO features, such that it produces outcomes which serve to further the political, hate or religious causes of their sponsors.

There are several ways to put on the appearance of conducting serious science, yet still effect outcomes which maintain alignment with the agency of your funders, sponsors, mentors or controlling authorities. Recent ethical evolution inside science, has highlighted the need for understanding that a researcher’s simply having calculated a p-value, applied an arrival distribution or bounded an estimate inside a confidence interval, does not necessarily mean that they have developed a sound basis from which to draw any quality inference. In similar philosophy, one can develop a study – and completely mislead the scientific community as to the nature of reality inside a given issue of contention or science.

We are all familiar with the trick of falsely calling a ‘survey of study abstracts’, or a meta-synthesis of best evidence, or an opinion piece summarizing a body of study from one person’s point of view – a ‘meta-analysis’. A meta-analysis combines congruent study designs and bodies of equivalent data, in order to improve the statistical power of the combined entailed analyses.1 The fake forms of meta-analysis do no such thing. A meta-analysis is a secondary or filtered systematic review which only bears leveraged strength in the instance wherein randomized controlled trials or longitudinal studies of the same species, are able to be combined in order to derive this higher statistical power. Every other flavor of such ‘blending of study’, does not accomplish such an objective. Such blending may, and this is important, actually serve to reduce the probative power of the systematic review itself. Nonetheless, you will find less-than-ethical scientists trying to push their opinion/summary articles upon the community as if they reflected through convenient misnomer, this ‘most rigorous form of study design’. One can find an example of this within the study: Taylor, Swerdfeger, Eslick; An evidence-based meta-analysis of case-control and cohort studies; Elsevier, 2014.2

This equivocal sleight-of-hand stands as merely one example of the games played within the agency-influenced domains of science. With regard to manipulating study design in order to effect a desired scientific outcome, there are several means of accomplishing this feat. Most notably the following methods, which are all called collectively, torfuscation. Torfuscation involves employing a less rigorous study type (lower rank on the Chart below), an ineffective study design, or a type of flawed methodical PICO-time analysis, which will serve most often to weaken the probative potential of a study which could ostensibly serve to produce an outcome which threatens its sponsors.


/philosophy : pseudoscience : study fraud : Saxon : ‘hide in the bog’/ : pseudoscience or obfuscation enacted through a Nelsonian knowledge masquerade of scientific protocol and study design. Inappropriate, manipulated or shallow study design crafted so as to obscure or avoid a targeted/disliked inference. A process, contended to be science, wherein one develops a conclusion through cataloging study artifice or observation noise as valid data. Invalid observations which can be parlayed into becoming evidence of absence or evidence of existence as one desires – by accepting only the appropriate hit or miss grouping one desires as basis to support an a priori preference, and as well avoid any further needed ex ante proof.  A refined form of praedicate evidentia or utile abstentia employed through using less rigorous or probative methods of study than are requisite under otherwise ethical science.  Exploitation of study noise generated through first level ‘big data’ or agency-influenced ‘meta-synthesis’, as the ‘evidence’ that no further or deeper study is therefore warranted – and moreover that research of the subject entailed is now socially embargoed.

Study design which exploits the weakness potential entailed inside the PICO-time Study Design Development Model3 (see Study to Inference Strength and Risk Chart below), through the manipulation of the study

P – patient, problem or population
I – intervention, indicator
C – comparison, control or comparator
O – outcome, or
time – time series

Which seeks to compromise the outcome or conclusion in terms of the study usage; more specifically: prevention, screening, diagnostic, treatment, quality of life, compassionate use, expanded access, superiority, non-inferiority and or equivalence.

Meta-Garbage, Deescalation and PICO-time Manipulation

One example of tampering with the PICO-time attributes of a study, would consist of the circumstance wherein only medical plan completed diagnostic data is used as the sample base for a retrospective observational cohort study’s ‘outcome’ data. Such data is highly likely to be incomplete or skewed in a non-probative direction, under a condition of linear induction (a weaker form of inference) and utile abstentia (a method of exclusion bias through furtive data-source selection). In similar fashion and as example, if the average age of outcome diagnosis is 5.5 years, and the average slack time between diagnosis and first possible recording into a medical plan database is 4 to 18 months, then a constraining of the time-series involved inside a study examining that data, to 4.5 years, is an act of incompetent or malicious study design. But you will find both of these tricks to be common in studies wherein a potential outcome is threatening to a study’s sponsors; agents who hope to prove by modus absens shallow and linear inductive inference that the subject can be embargoed from then on. Just such a study can be found here: Madsen, Hviid; A Population-Based Study of Measles, Mumps, and Rubella Vaccination and Autism, 2002.4 A study may also be downgraded (lower on the chart below), and purposely forced to employ a lesser form of design probative strength (Levels 1 – 7); precisely because its sponsors suspect the possibility of a valid risk they do not want exposed. This is very similar to a downgrading in inference method called methodical deescalation – a common trick of professional pseudoscience. One may also notice that often, studies employing these three tricks are held as proprietary, concealed from the public during the critical study design phase. This is purposeful. This is oppression in the name of science. One may also notice that the ‘meta-analysis’ decried earlier in this article, cited this very study just mentioned as a ‘best evidence study’ inside its systematic review. If you meta-study garbage, you will produce meta-garbage as well (see Secondary Study in the Chart below).

The following is The Ethical Skeptic’s chart indexing study design against mode of inference, strength and its risk in torfuscation. It is a handy tool for helping spot torfuscation of the three example types elicited above, and more. The study types are ranked from top to bottom in terms of Level in probative strength (1 – 7), and as well are arranged into Direct, Analytical and Descriptive study groupings by color. Torfuscation involves the selection of a study type with a probative power lower down on the chart, when a higher probative level of study was available and/or warranted; as well as in tampering with the PICO-time risk elements (right side of chart under the yellow header) characteristic of each study type so as to weaken its overall ability to indicate a potential disliked outcome. The Chart is followed up by a series of definitions for each study type listed. The myriad sources for this compiled set of industry material are listed at the end of this article – however, it should be noted that the sources cited did not agree with each other on the material/level, structure nor definitions of various study designs. Therefore modifications and selections were made as to the attributes of study, which allowed for the entire set of alternatives/definitions to come into synchrony with each other – with minimal overlap and confusion. So you will not find 100% of this chart replicated inside any single resource or textbook. (note: My past lab experience has been mostly in non-randomized controlled factorial trial study – whose probative successes were fed into a predictive model, then confirmed by single mechanistic lab tests. I found this approach to be highly effective in my past professional work. But that lab protocol may not apply to other types of study challenge and could be misleading if applied as a panacea. Hence the need for the chart below.)

Study Design Type Definitions


Experimental– A study which involves a direct physical test of the material or principal question being asked.

Mechanistic/Lab – A direct study which examines a physical attribute or mechanism inside a controlled closed environment, influencing a single input variable, while observing a single output variable – both related to that attribute or mechanism.

Controlled Trial

Randomized (Randomized Controlled Trial) – A study in which people are allocated at random (by chance alone) to receive one of several clinical interventions. One of these interventions is the standard of comparison or the ‘control’. The control may be a standard practice, a placebo (“sugar pill”), or no intervention at all.

Non-Randomized Controlled Trial – A study in which people are allocated by a discriminating factor (not bias), to receive one of several clinical interventions. One of these interventions is the standard of comparison or the ‘control’. The control may be a standard practice, a placebo (“sugar pill”), or no intervention at all.

Parallel – A type of controlled trial where two groups of treatments, A and B, are given so that one group receives only A while another group receives only B. Other names for this type of study include “between patient” and “non-crossover” studies.

Crossover – A longitudinal direct study in which subjects receive a sequence of different treatments (or exposures). In a randomized controlled trial with repeated measures design, the same measures are collected multiple times for each subject. A crossover trial has a repeated measures design in which each patient is assigned to a sequence of two or more treatments, of which one may either be a standard treatment or a placebo. Nearly all crossover controlled trial studies are designed to have balance, whereby all subjects receive the same number of treatments and participate for the same number of periods. In most crossover trials each subject receives all treatments, in a random order.

Factorial – A factorial study is an experiment whose design consists of two or more factors, each with discrete possible values or ‘levels’, and whose experimental units take on all possible combinations of these levels across all such factors. A full factorial design may also be called a fully-crossed design. Such an experiment allows the investigator to study the effect of each factor on the response variable or outcome, as well as the effects of interactions between factors on the response variable or outcome.

Blind Trial – A trial or experiment in which information about the test is masked (kept) from the participant (single blind) and/or the test administerer (double blind), to reduce or eliminate bias, until after a trial outcome is known.

Open Trial – A type of non-randomized controlled trial in which both the researchers and participants know which treatment is being administered.

Placebo-Control Trial – A study which blindly and randomly allocates similar patients to a control group that receives a placebo and an experimental test group. Therein investigators can ensure that any possible placebo effect will be minimized in the final statistical analysis.

Interventional (Before and After/Interrupted Time Series/Historical Control) – A study in which observations are made before and after the implementation of an intervention, both in a group that receives the intervention and in a control group that does not. A study that uses observations at multiple time points before and after an intervention (the ‘interruption’). The design attempts to detect whether the intervention has had an effect significantly greater than any underlying trend over time.

Adaptive Clinical Trial – A controlled trial that evaluates a medical device or treatment by observing participant outcomes (and possibly other measures, such as side-effects) along a prescribed schedule, and modifying parameters of the trial protocol in accord with those observations. The adaptation process generally continues throughout the trial, as prescribed in the trial protocol. Modifications may include dosage, sample size, drug undergoing trial, patient selection criteria or treatment mix. In some cases, trials have become an ongoing process that regularly adds and drops therapies and patient groups as more information is gained. Importantly, the trial protocol is set before the trial begins; the protocol pre-specifies the adaptation schedule and processes. 

Observational – Analytical

Cohort/Panel (Longitudinal) – A study in which a defined group of people (the cohort – a group of people who share a defining characteristic, typically those who experienced a common event in a selected period) is followed over time, to examine associations between different interventions received and subsequent outcomes.  

Prospective – A cohort study which recruits participants before any intervention and follows them into the future.

Retrospective – A cohort study which identifies subjects from past records describing the interventions received and follows them from the time of those records.

Time-Series – A cohort study which identifies subjects from a particular segment in time following an intervention (which may have also occurred in a time series) and follows them during only the duration of that time segment. Relies upon robust intervention and subject tracking databases. For example, comparing lung health to pollution during a segment in time.

Cross-Sectional/Transverse/Prevalence – A study that collects information on interventions (past or present) and current health outcomes, i.e. restricted to health states, for a group of people at a particular point in time, to examine associations between the outcomes and exposure to interventions.

Case-Control – A study that compares people with a specific outcome of interest (‘cases’) with people from the same source population but without that outcome (‘controls’), to examine the association between the outcome and prior exposure (e.g. having an intervention). This design is particularly useful when the outcome is rare.

Nested Case-Control – A study wherein cases of a health outcome that occur in a defined cohort are identified and, for each, a specified number of matched controls is selected from among those in the cohort who have not developed the health outcome by the time of occurrence in the case. For many research questions, the nested case-control design potentially offers impressive reductions in costs and efforts of data collection and analysis compared with the full case-control or cohort approach, with relatively minor loss in statistical efficiency.

Community Survey – An observational study wherein a targeted cohort or panel is given a set of questions regarding both interventions and observed outcomes over the life or a defined time period of the person, child or other close family member. These are often conducted in conjunction with another disciplined polling process (such as a census or general medical plan survey) so as to reduce statistical design bias or error.

Ecological (Correlational) – A study of risk-modifying factors on health or other outcomes based on populations defined either geographically or temporally. Both risk-modifying factors and outcomes are averaged or are linear regressed for the populations in each geographical or temporal unit and then compared using standard statistical methods.

Observational – Descriptive

Population – A study of a group of individuals taken from the general population who share a common characteristic, such as age, sex, or health condition. This group may be studied for different reasons, such as their response to a drug or risk of getting a disease. 

Case Series – Observations are made on a series of specific individuals, usually all receiving the same intervention, before and after an intervention but with no control group.

Case Report – Observation is made on a specific individual, receiving an intervention, before and after an intervention but with no control group/person other than the general population.


Systematic Review/Objective Meta-Analysis – A method for systematically combining pertinent qualitative and quantitative study data from several selected studies to develop a single conclusion that has greater statistical power. This conclusion is statistically stronger than the analysis of any single study, due to increased numbers of subjects, greater diversity among subjects, or accumulated effects and results. However, researchers must ensure that the quantitative and study design attributes of the contained studies all match, in order to retain and enhance the statistical power entailed. Mixing lesser rigorous or incongruent studies with more rigorous studies will only result in a meta-analysis which bears the statistical power of only a portion of the studies, or of the least rigorous study type contained, in decreasing order along the following general types of study:

Controlled Trial/Mechanism

Interpretive/Abstract ‘Meta-Synthesis’ – A study which surveys the conclusion or abstract of a pool of studies in order to determine the study authors’ conclusions along a particular line of conjecture or deliberation. This may include a priori conclusions or author preferences disclosed inside the abstract of each study, which were not necessarily derived as an outcome of the study itself. This study may tally a ‘best evidence’ subset of studies within the overall survey group, which stand as superior in their representation of the conclusion, methodology undertaken or breadth in addressing the issue at hand.

Editorial/Expert Opinion – A summary article generally citing both scientific outcomes and opinion, issued by an expert within a given field, currently active and engaged in research inside that field. The article may or may not refer to specific examples of studies, which support an opinion that a consilience of evidence points in a given direction regarding an issue of deliberation. The author will typically delineate a circumstance of study outcome, consilience or consensus as separate from their personal professional opinion.

Critical Review/Skeptic Opinion – A self-identified skeptic or science enthusiast, applies a priori thinking with no ex ante accountability, in order to arrive at a conclusion. The reviewer may or may not cite a couple examples or studies to back their conclusion.

Sources: 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

     How to MLA cite this article:

The Ethical Skeptic, “Torfuscation – Gaming Study Design to Effect an Outcome”; The Ethical Skeptic, WordPress, 15 Apr 2019; Web,

April 15, 2019 Posted by | Agenda Propaganda, Institutional Mandates, Tradecraft SSkepticism | , , | 2 Comments

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