One key, if not the primary form of invalid inference on the part of fake skeptics, resides in the methodology of panductive inference. A pretense of Popper demarcation, panduction is employed as a masquerade of science in the form of false deduction. Moreover it constitutes an artifice which establishes the purported truth of a favored hypothesis by means of the extraordinary claim of having falsified every competing idea in one fell swoop of rationality. Panduction is the most common form of pseudoscience.

Having just finished my review of the Court’s definition of malice and oppression in the name of science, as outlined in the Dewayne Johnson vs. Monsanto Company case, my thinking broached a category of pseudoscience which is practiced by parties who share similar motivations to the defendant in that landmark trial. Have you ever been witness to a fake skeptic who sought to bundle all ‘believers’ as one big deluded group, who all hold or venerate the same credulous beliefs? Have you ever read a skeptic blog, claiming a litany of subjects to be ‘woo’ – yet fully unable to cite any evidence whatsoever which served to epistemologically classify that embargoed realm of ideas under such an easy categorization of dismissal? What you are witness to, is the single most common, insidious and pretend-science habit of fake skeptics, panduction.

It’s not that all the material contained in the embargoed hypotheses realm has merit. Most of it does not. But what is comprised therein, even and especially in being found wrong, resides along the frontier of new discovery. You will soon learn on this journey of ethical skepticism, that discovery is not the goal of the social skeptic; rather that is exactly what they have been commissioned to obfuscate.

Science to them is nothing more than an identity which demands ‘I am right’.

There exist three forms of valid inference, in order of increasing scientific gravitas: abduction, induction and deduction. Cleverly downgrading science along these forms of inference in order to avoid more effective inference methods which might reveal a disliked outcome, constitutes another form of fallacy altogether, called methodical deescalation.  We shall not address methodical deescalation here, but rather, a fourth common form of inference, which is entirely invalid in itself. Panduction is a form of ficta rationalitas; an invalid attempt to employ critical failures in logic and evidence in order to condemn a broad array of ideas, opinions, hypotheses, constructs and avenues of research as being Popper falsified; when in fact nothing of the sort has been attained. It is a method of proving yourself correct, by impugning everyone and everything besides the idea you seek to protect, all in one incredible feat of armchair or bar-stool reasoning. It is often peddled as critical thinking by fake skeptics.

Panduction is a form of syllogism derived from extreme instances of Appeal to Ignorance, Inverse Negation and/or Bucket Characterization from a Negative Premise. It constitutes a shortcut attempt to promote one idea at the expense of all other ideas, or kill an array of ideas one finds objectionable. Nihilists employ panduction for example, as a means to ‘prove’ that nothing exists aside from the monist and material entities which they approve as real. They maintain the fantasy that science has proved that everything aside from what they believe, is false by a Popperian standard of science – i.e. deducted. This is panduction.

Panduction

/philosophy : invalid inference/ : an invalid form of inference which is spun in the form of pseudo-deductive study. Inference which seeks to falsify in one fell swoop ‘everything but what my club believes’ as constituting one group of bad people, who all believe the same wrong and correlated things – this is the warning flag of panductive pseudo-theory. No follow up series studies nor replication methodology can be derived from this type of ‘study’, which in essence serves to make it pseudoscience.  This is a common ‘study’ format which is conducted by social skeptics masquerading as scientists, to pan people and subjects they dislike.

There are three general types of Panduction. In its essence, panduction is any form of inference used to pan an entire array of theories, constructs, ideas and beliefs (save for one favored and often hidden one), by means of the following technique groupings:

1. Extrapolate and Bundle from Unsound Premise
2. Impugn through Invalid Syllogism
3. Mischaracterize though False Observation

The first is executed through attempting to falsify entire subject horizons through bad extrapolation. The second involves poorly developed philosophies of denial. Finally the third involves the process of converting disliked observations or failures to observe, into favorable observations:

Panduction Type I

Extrapolate and Bundle from Unsound Premise – Bucket Characterization through Invalid Observation – using a small, targeted or irrelevant sample of linear observations to extrapolate and further characterize an entire asymmetric array of ideas other than a preferred concealed one. Falsification by:

Absence of Observation (praedicate evidentia modus ponens) – any of several forms of exaggeration or avoidance in qualifying a lack of evidence, logical calculus or soundness inside an argument. Any form of argument which claims a proposition consequent ‘Q’, which also features a lack of qualifying modus ponens, ‘If P then’ premise in its expression – rather, implying ‘If P then’ as its qualifying antecedent. This as a means of surreptitiously avoiding a lack of soundness or lack of logical calculus inside that argument; and moreover, enforcing only its conclusion ‘Q’ instead. A ‘There is not evidence for…’ claim made inside a condition of little study or full absence of any study whatsoever.

Insignificant Observation (praedicate evidentia) – hyperbole in extrapolating or overestimating the gravitas of evidence supporting a specific claim, when only one examination of merit has been conducted, insufficient hypothesis reduction has been performed on the topic, a plurality of data exists but few questions have been asked, few dissenting or negative studies have been published, or few or no such studies have indeed been conducted at all.

Anecdote Error – the abuse of anecdote in order to squelch ideas and panduct an entire realm of ideas. This comes in two forms:

Type I – a refusal to follow up on an observation or replicate an experiment, does not relegate the data involved to an instance of anecdote.

Type II – an anecdote cannot be employed to force a conclusion, such as using it as an example to condemn a group of persons or topics – but an anecdote can be employed however to introduce Ockham’s Razor plurality. This is a critical distinction which social skeptics conveniently do not realize nor employ.

Cherry Picking – pointing to a talking sheet of handpicked or commonly circulated individual cases or data that seem to confirm a particular position, while ignoring or denying a significant portion of related context cases or data that may contradict that position.

Straw Man – misrepresentation of either an ally or opponent’s position, argument or fabrication of such in absence of any stated opinion.

Dichotomy of Specific Descriptives – a form of panduction, wherein anecdotes are employed to force a conclusion about a broad array of opponents, yet are never used to apply any conclusion about self, or one’s favored club. Specific bad things are only done by the bad people, but very general descriptives of good, apply when describing one’s self or club. Specifics on others who play inside disapproved subjects, general nebulous descriptives on self identity and how it is acceptable ‘science’ or ‘skepticism’.

Associative Condemnation (Bucket Characterization and Bundling) – the attempt to link controversial subject A with personally disliked persons who support subject B, in an effort to impute falsehood to subject B and frame its supporters as whackos. Guilt through bundling association and lumping all subjects into one subjective group of believers. This will often involve a context shift or definition expansion in a key word as part of the justification. Spinning for example, the idea that those who research pesticide contribution to cancer, are also therefore flat Earther’s.

Panduction Type II

Impugn through Invalid Syllogism – Negative Assertion from a Pluralistic, Circular or Equivocal Premise – defining a set of exclusive premises to which the contrapositive applies, and which serves to condemn all other conditions.

Example (Note that ‘paranormal’ here is defined as that which a nihilist rejects a being even remotely possible):

All true scientists are necessarily skeptics. True skeptics do not believe in the paranormal. Therefore no true scientist can research the paranormal.

All subjects which are true are necessarily not paranormal. True researchers investigate necessarily true subjects. Therefore to investigate a paranormal subject makes one not a true researcher.

All false researchers are believers. All believers tend to believe the same things. Therefore all false researchers believe all the same things.

Evidence only comes from true research. A paranormal investigator is not a true researcher. Therefore no evidence can come from a paranormal subject.

One may observe that the above four examples, thought which rules social skepticism today, are circular in syllogism and can only serve to produce the single answer which was sought in the first place. But ruling out entire domains of theory, thought, construct, idea and effort, one has essentially panned everything, except that which one desires to be indeed true (without saying as much).  It would be like Christianity pointing out that every single thought on the part of mankind, is invalid, except what is in the Bible. The Bible being the codification equivalent of the above four circular syllogisms, into a single document.

Panduction Type III

Mischaracterize through False Observation – Affirmation from Manufacturing False Positives or Negatives – manipulating the absence of data or the erroneous nature of various data collection channels to produce false negatives or positives.

Panduction Type III is an extreme form of an appeal to ignorance. In an appeal to ignorance, one is faced with observations of negative conditions which could tempt one to infer inductively that there exists nothing but the negative condition itself. An appeal to ignorance simply reveals one of the weaknesses of inductive inference.  Let’s say that I find a field which a variety of regional crow murders frequent. So I position a visual motion detection camera on a pole across from the field in order to observe crow murders who frequent that field. In my first measurement and observation instance, I observe all of the crows to be black. Let us further then assume that I then repeat that observation exercise 200 times on that same field over the years. From this data I may well develop a hypothesis that includes a testable mechanism in which I assert that all crows are black. I have observed a large population size, and all of my observations were successful, to wit: I found 120,000 crows to all be black. This is inductive inference. Even though this technically would constitute an appeal to ignorance, it is not outside of reason to assert a new null hypothesis, that all crows are black – because my inference was derived from the research and was not a priori favored. I am not seeking to protect the idea that all crows are black simply because I or my club status are threatened by the specter of a white crow. The appeal to ignorance fallacy is merely a triviality in this case, and does not ‘disprove’ the null (see the Appeal to Fallacy). Rather it stands as a caution, that plurality should be monitored regarding the issue of all crows being black.

But, what if I become so convinced that the null hypothesis in this case is the ‘true’ hypothesis, or even preferred that idea in advance because I was a member of a club which uses a black crow as its symbol? In such a case I approach the argument with an a priori belief which I must protect. I begin to craft my experimental interpretation of measurement such that it conforms to this a priori mandate in understanding. This will serve to produce four species of study observation procedural error, which are in fact, pseudoscience; the clever masquerade of science and knowledge:

A.  Affirmation from Result Conversion  – employing a priori assumptions as filters or data converters, in order to produce desired observational outcomes.

1.  Conversion by a priori Assumption (post hoc ergo propter hoc). But what if the field I selected, bore a nasty weather phenomenon of fog, on an every other day basis. Further then, this fog obscured a good view of the field, to the point where I could only observe the glint of sunlight off the crow’s wings, which causes several of them to appear white, even though they are indeed black. But because I know there are no white crows now, I use a conversion algorithm I developed to count the glints inside the fog, and register them as observations of black crows? Even though a white crow could also cause the same glint. I have created false positives by corrupted method.

2.  Conversion by Converse a priori Assumption (propter hoc ergo hoc – aka plausible deniability). Further then, what if I assumed that any time I observed a white crow, that this would therefore be an indication that fog was present, and a condition of Data Conversion by a priori Assumption was therefore assumed to be in play? I would henceforth, never be able to observe a white crow at all, finding only results which conform to the null hypothesis, which would now be an Omega Hypothesis (see The Art of Professional Lying: The Tower of Wrong).

Example: Viking Mars Lander Data Manipulation

Two Mars Viking Landers were sent to Mars, in part to study for signs of life. NASA researchers took soil samples the Viking landers scooped from the surface and mixed it with nutrient-rich water. If the soil had life, the theory went that the soil’s microbes would metabolize the nutrients in the water and release a certain signature of radioactive molecules. To their pleasant surprise, the nutrients metabolized and radioactive molecules were released – suggesting that Mars’ soil contained life. However, the Viking probes’ other two experiments found no trace of organic material, which prompted the question: If there were no organic materials, what could be doing the metabolizing? So by assumption, the positive results from the metabolism test, were dismissed as derivative from some other chemical reaction, which has not been identified to date. The study was used as rational basis from which to decline further search for life on Mars, when it should have been appropriately deemed ‘inconclusive’ instead (especially in light of our finding organic chemicals on Mars in the last several months)¹

B. Affirmation from Observation Failure Conversion – errors in observation are counted as observations of negative conditions, further then used as data or as a data screening criterion.

Continuing with our earlier example, what if on 80% of the days in which I observed the field full of crows, the camera malfunctioned and errantly pointed into the woods to the side, and I was fully unable to make observations at all on those days? Further then, what if I counted those non-observing days as ‘black crow’ observation days, simply because I had defined a black crow as being the ‘absence of a white crow’ (pseudo-Bayesian science) instead of being constrained to only the actual observation of an actual physical white crow? Moreover, what if, because of the unreliability of this particular camera, any observations of white crows it presented were tossed out, so as to prefer observations from ‘reliable’ cameras only? This too, is pseudoscience in two forms:

1.  Observation Failure as Observation of a Negative (utile absentia). – a study which observes false absences of data or creates artificial absence noise through improper study design, and further then assumes such error to represent verified negative observations. A study containing field or set data in which there exists a risk that absences in measurement data, will be caused by external factors which artificially serve to make the evidence absent, through risk of failure of detection/collection/retention of that data. The absences of data, rather than being filtered out of analysis, are fallaciously presumed to constitute bonafide observations of negatives. This is improper study design which will often serve to produce an inversion effect (curative effect) in such a study’s final results. Similar to torfuscation.

2.  Observation Failure as Basis for Selecting For Reliable over Probative Data (Cherry Sorting) – when one applies the categorization of ‘anecdote’ to screen out unwanted observations and data. Based upon the a priori and often subjective claim that the observation was ‘not reliable’. Ignores the probative value of the observation and the ability to later compare other data in order to increase its reliability in a more objective fashion, in favor of assimilating an intelligence base which is not highly probative, and can be reduced only through statistical analytics – likely then only serving to prove what one was looking for in the first place (aka pseudo-theory).

These two forms of conversion of observation failures into evidence in favor of a particular position, are highlighted no better than studies which favor healthcare plan diagnoses over cohort and patient input surveys. Studies such as the Dutch MMR-Autism Statistical Meta-Analysis or the Jain-Marshall Autism Statistical Analysis failed precisely because of the two above fallacious methods regarding the introduction of data. Relying only upon statistical analytics of risk-sculpted and cherry sorted data, rather than direct critical path observation.

 Example: Jain-Marshall Autism Study

Why is the 2015 Jain-Marshall Study of weak probative value? Because it took third party, unqualified (health care plan) sample interpretations of absences (these are not observations – they are ‘lack-of’ observations – which are not probative data to an intelligence specialist – nor to a scientist – see pseudo-theory) from vaccinated and non-vaccinated children’s final medical diagnoses at ages 2, 3, and 5. It treated failures in the data collection of these healthcare databases, as observations of negative results (utile absentia). A similar data vulnerability to the National Vaccine Injury Compensation System’s ‘self-volunteering’ of information and limitation of detection to within 3 years. This favors a bad, non-probative data repository, simply because of its perception as being ‘reliable’ as a source of data. This fails to catch 99% of signal observations (Cherry Sorting), and there is good demonstrable record of that failure to detect actual injury circumstances.²

One might chuckle at the face value ludicrousness of either Panduction Type III A and B. But Panduction Type III is regularly practiced inside of peer reviewed journals of science. Its wares constitute the most insidious form of malicious and oppressive fake science. One can certainly never expect a journalist to understand why this form of panduction is invalid, but certainly one should expect it of their peer review scientists – those who are there to protect the public from bad science. And of course, one should expect it from an ethical skeptic.

The Ethical Skeptic, “Panduction: The Invalid Form of Inference” The Ethical Skeptic, WordPress, 31 Aug 2018; Web, https://wp.me/p17q0e-8c6