Poisoning the Well Fallacy Examples
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Argumentation and Fallacies in Creationist Writings Against Evolutionary Theory Petteri Nieminen1,2* and Anne-Mari Mustonen1
Nieminen and Mustonen Evolution: Education and Outreach 2014, 7:11 http://www.evolution-outreach.com/content/7/1/11 RESEARCH ARTICLE Open Access Argumentation and fallacies in creationist writings against evolutionary theory Petteri Nieminen1,2* and Anne-Mari Mustonen1 Abstract Background: The creationist–evolutionist conflict is perhaps the most significant example of a debate about a well-supported scientific theory not readily accepted by the public. Methods: We analyzed creationist texts according to type (young earth creationism, old earth creationism or intelligent design) and context (with or without discussion of “scientific” data). Results: The analysis revealed numerous fallacies including the direct ad hominem—portraying evolutionists as racists, unreliable or gullible—and the indirect ad hominem, where evolutionists are accused of breaking the rules of debate that they themselves have dictated. Poisoning the well fallacy stated that evolutionists would not consider supernatural explanations in any situation due to their pre-existing refusal of theism. Appeals to consequences and guilt by association linked evolutionary theory to atrocities, and slippery slopes to abortion, euthanasia and genocide. False dilemmas, hasty generalizations and straw man fallacies were also common. The prevalence of these fallacies was equal in young earth creationism and intelligent design/old earth creationism. The direct and indirect ad hominem were also prevalent in pro-evolutionary texts. Conclusions: While the fallacious arguments are irrelevant when discussing evolutionary theory from the scientific point of view, they can be effective for the reception of creationist claims, especially if the audience has biases. Thus, the recognition of these fallacies and their dismissal as irrelevant should be accompanied by attempts to avoid counter-fallacies and by the recognition of the context, in which the fallacies are presented. -
Informal Fallacies 2
Ashford University - Ed Tech | Informal_Fallacies_2 JUSTIN Hi, everybody. This is going to be a continuation of the informal logical fallacy HARRISON: discussion. The next one we're going to be talking about is the relativist fallacy. This is a common one that you see. Even in intellectual circles, you see really smart people falling into this fallacy. Well, I guess you can be consistent, but it's very hard to be consistent. The relativist fallacy occurs when you say that, for example, different cultures have different beliefs so what's right in one culture or what's right for one group is right and good. And then something that's opposite in another group is considered right and good. And those two things are right and good for both cultures or groups or whatever it might be. Well, there are different types of relativism, but cultural relativism would say things like, well, we can't judge other cultures because their actions are right based on their own definitions of what is right. And our definitions of what is right and wrong are different. Therefore, what they believe is right is right and what we believe is right is right. And hopefully you can see the problem with this is that-- let's say that we're confronting a culture that subjugates women. And in that culture, it is right or morally acceptable to gang rape a woman, which is actually-- this happens in the world-- when she's been accused of some crime-- often a crime that she didn't commit, but she's just been accused of it. -
Section 6: Reporting Likelihood Ratios Components
Section 6: Reporting Likelihood Ratios Components • Hierarchy of propositions • Formulating propositions • Communicating LRs Section 6 Slide 2 Likelihood Ratio The LR assigns a numerical value in favor or against one propo- sition over another: Pr(EjHp;I) LR = ; Pr(EjHd;I) where Hp typically aligns with the prosecution case, Hd is a reasonable alternative consistent with the defense case, and I is the relevant background information. Section 6 Slide 3 Setting Propositions • The value for the LR will depend on the propositions chosen: different sets of propositions will lead to different LRs. • Choosing the appropriate pair of propositions can therefore be just as important as the DNA analysis itself. Section 6 Slide 4 Hierarchy of Propositions Evett & Cook (1998) established the following hierarchy of propositions: Level Scale Example III Offense Hp: The suspect raped the complainant. Hd: Some other person raped the complainant. II Activity Hp: The suspect had intercourse with the complainant. Hd: Some other person had intercourse with the complainant. I Source Hp: The semen came from the suspect. Hd: The semen came from an unknown person. 0 Sub-source Hp: The DNA in the sample came from the suspect. Hd: The DNA in the sample came from an unknown person. Section 6 Slide 5 Hierarchy of Propositions • The offense level deals with the ultimate issue of guilt/ innocence, which are outside the domain of the forensic scientist. • The activity level associates a DNA profile or evidence source with the crime itself, and there may be occasions where a scientist can address this level. • The source level associates a DNA profile or evidence item with a particular body fluid or individual source. -
35 Fallacies
THIRTY-TWO COMMON FALLACIES EXPLAINED L. VAN WARREN Introduction If you watch TV, engage in debate, logic, or politics you have encountered the fallacies of: Bandwagon – "Everybody is doing it". Ad Hominum – "Attack the person instead of the argument". Celebrity – "The person is famous, it must be true". If you have studied how magicians ply their trade, you may be familiar with: Sleight - The use of dexterity or cunning, esp. to deceive. Feint - Make a deceptive or distracting movement. Misdirection - To direct wrongly. Deception - To cause to believe what is not true; mislead. Fallacious systems of reasoning pervade marketing, advertising and sales. "Get Rich Quick", phone card & real estate scams, pyramid schemes, chain letters, the list goes on. Because fallacy is common, you might want to recognize them. There is no world as vulnerable to fallacy as the religious world. Because there is no direct measure of whether a statement is factual, best practices of reasoning are replaced be replaced by "logical drift". Those who are political or religious should be aware of their vulnerability to, and exportation of, fallacy. The film, "Roshomon", by the Japanese director Akira Kurisawa, is an excellent study in fallacy. List of Fallacies BLACK-AND-WHITE Classifying a middle point between extremes as one of the extremes. Example: "You are either a conservative or a liberal" AD BACULUM Using force to gain acceptance of the argument. Example: "Convert or Perish" AD HOMINEM Attacking the person instead of their argument. Example: "John is inferior, he has blue eyes" AD IGNORANTIAM Arguing something is true because it hasn't been proven false. -
89% of Introduction-To-Psychology Textbooks That Define Or Explain
AMPXXX10.1177/2515245919858072Cassidy et al.Failing Grade 858072research-article2019 ASSOCIATION FOR General Article PSYCHOLOGICAL SCIENCE Advances in Methods and Practices in Psychological Science Failing Grade: 89% of Introduction-to- 2019, Vol. 2(3) 233 –239 © The Author(s) 2019 Article reuse guidelines: Psychology Textbooks That Define sagepub.com/journals-permissions DOI:https://doi.org/10.1177/2515245919858072 10.1177/2515245919858072 or Explain Statistical Significance www.psychologicalscience.org/AMPPS Do So Incorrectly Scott A. Cassidy, Ralitza Dimova, Benjamin Giguère, Jeffrey R. Spence , and David J. Stanley Department of Psychology, University of Guelph Abstract Null-hypothesis significance testing (NHST) is commonly used in psychology; however, it is widely acknowledged that NHST is not well understood by either psychology professors or psychology students. In the current study, we investigated whether introduction-to-psychology textbooks accurately define and explain statistical significance. We examined 30 introductory-psychology textbooks, including the best-selling books from the United States and Canada, and found that 89% incorrectly defined or explained statistical significance. Incorrect definitions and explanations were most often consistent with the odds-against-chance fallacy. These results suggest that it is common for introduction- to-psychology students to be taught incorrect interpretations of statistical significance. We hope that our results will create awareness among authors of introductory-psychology books -
Common Reasoning Mistakes
Common Fallacies (mistakes of reasoning) The fallacy fallacy • There is danger even in the study of fallacies. This study involves identifying certain patterns of reasoning as fallacies. Each pattern has a name. E.g. an argument that attacks a person is ad hominem. But ad hominem arguments are not always fallacies! • Rejecting an argument as a (named) fallacy, based on its pattern alone, is a fallacy that we might call the fallacy fallacy. • In general, an ad hominem is only legitimate when attacking an argument from authority. • But not all such attacks on authority are legitimate. They can be made on irrelevant grounds. Irrelevant ad hominem E.g. Einstein’s physics was attacked on the basis of Einstein being Jewish. Thomas Powers, Heisenberg’s War, p. 41 Fallacy? • Alliance leader Stockwell Day argues that Canada should increase its military expenditure now, by at least 20%, in order to continue to meet our NATO obligations five years from now. But Day is a fundamentalist who thinks the universe is only 6,000 years old! Clearly his view can be dismissed. • Mr. Wilson, in his letter of January 16, argues that it would be counter-productive to yield to the demands of the hostage takers. He does not, I take it, have a son or daughter among the hostages. As such a parent, I am repelled by his callous attitude. My daughter could well be the next innocent victim of these terrorists, but Wilson apparently doesn’t give a damn about this. 1. Comment on the following ad hominem (to the person) arguments, explaining why they are, or are not, reasonable. -
Explicit Examples of Logical Fallacies in Love Is a Fallacy by Max Shulman Foundations – Part of the Easy Peasy All-In-One Homeschool
Explicit examples of logical fallacies in Love is a Fallacy by Max Shulman Foundations – Part of the Easy Peasy All-in-One Homeschool A dicto simpliciter ("an argument based on an unqualified generalization") - the example given in the story is: Exercise is good. Therefore everybody should exercise. Hasty generalization (or "fallacy of insufficient sample") - example given in the story is “You can speak French, I can't speak French, Petey Burch can't speak French. I must therefore conclude that nobody at the University of Minnesota can speak French.” If most of the people the author (Dobie Gillis) knows cannot speak French he concludes that no one at the college can speak French. OR "My dear," I said, favoring her with a smile, "we have now spent five evenings together. We have gotten along, splendidly. It is clear that we are well matched." Post hoc ergo propter hoc ("after it, therefore because of it", or "confusing coincidental relationships with cause") - from the story: “Let's not take Bill on our picnic. Every time we take him out with us, it rains.” Contradictory Premises ("self-contradiction") - from the story: I do not see the contradictory premise in this story. The main contradiction would be that the author (Dobie Gillis) begins the story believing that love is logical and can be won through logic. However, the end of the story proves that love is not logical and Dobie’s original belief was a fallacy. Ad Misericordiam ("appeal to pity") - example given in the story: "A man applies for a job. When the boss asks him what his qualifications are, he replies the he has wife and six children at home, the wife is a helpless cripple, the children have nothing to eat, no clothes to wear, no shoes on their feet, there are no beds in the house, no coal in the cellar, and winter is coming." OR “Polly, I love you. -
Fallacies Are Deceptive Errors of Thinking
Fallacies are deceptive errors of thinking. A good argument should: 1. be deductively valid (or inductively strong) and have all true premises; 2. have its validity and truth-of-premises be as evident as possible to the parties involved; 3. be clearly stated (using understandable language and making clear what the premises and conclusion are); 4. avoid circularity, ambiguity, and emotional language; and 5. be relevant to the issue at hand. LogiCola R Pages 51–60 List of fallacies Circular (question begging): Assuming the truth of what has to be proved – or using A to prove B and then B to prove A. Ambiguous: Changing the meaning of a term or phrase within the argument. Appeal to emotion: Stirring up emotions instead of arguing in a logical manner. Beside the point: Arguing for a conclusion irrelevant to the issue at hand. Straw man: Misrepresenting an opponent’s views. LogiCola R Pages 51–60 Appeal to the crowd: Arguing that a view must be true because most people believe it. Opposition: Arguing that a view must be false because our opponents believe it. Genetic fallacy: Arguing that your view must be false because we can explain why you hold it. Appeal to ignorance: Arguing that a view must be false because no one has proved it. Post hoc ergo propter hoc: Arguing that, since A happened after B, thus A was caused by B. Part-whole: Arguing that what applies to the parts must apply to the whole – or vice versa. LogiCola R Pages 51–60 Appeal to authority: Appealing in an improper way to expert opinion. -
False Dilemma Wikipedia Contents
False dilemma Wikipedia Contents 1 False dilemma 1 1.1 Examples ............................................... 1 1.1.1 Morton's fork ......................................... 1 1.1.2 False choice .......................................... 2 1.1.3 Black-and-white thinking ................................... 2 1.2 See also ................................................ 2 1.3 References ............................................... 3 1.4 External links ............................................. 3 2 Affirmative action 4 2.1 Origins ................................................. 4 2.2 Women ................................................ 4 2.3 Quotas ................................................. 5 2.4 National approaches .......................................... 5 2.4.1 Africa ............................................ 5 2.4.2 Asia .............................................. 7 2.4.3 Europe ............................................ 8 2.4.4 North America ........................................ 10 2.4.5 Oceania ............................................ 11 2.4.6 South America ........................................ 11 2.5 International organizations ...................................... 11 2.5.1 United Nations ........................................ 12 2.6 Support ................................................ 12 2.6.1 Polls .............................................. 12 2.7 Criticism ............................................... 12 2.7.1 Mismatching ......................................... 13 2.8 See also -
The Justice Academy Journal Law and Justice Executive Series Special Edition
The Justice Academy Journal Law and Justice Executive Series Special Edition Critical Thinking, Common Fallacies, and Leadership One of my all-time favorite movies was Tom Clancy’s, Hunt for Red October. Within that movie there is a scene that I found fascinating within my capacity as a university professor teaching logic and statistics. The scene involves a JusticeAcademy.org meeting of top level decision makers who are gathered around a table in the basement of the Whitehouse, and after a briefing given by Jack Ryan pertain- he Justice Academy serves as a national repository ing to the design, construction, and launch of a new Russian submarine, the and portal for instructional programs and special- ized training materials that are produced by law National Security Advisor who is chairing the meeting asks Admiral Greer enforcement agencies, prosecutors, and the (the character played by James Earl Jones) what conclusions he has made. courts and makes these educational assets availa- ble to the general law enforcement community, at The Admiral responded, “Sir, the data support no conclusions as of yet”. I no charge. thought this statement was one of the more profound expressions that I had JusticeAcademy.org also sponsors comprehensive research into a variety of issues relative to the law ever heard in any movie. What an astonishing and refreshing response I and justice professions, as well as authoring and thought to myself. He was exactly right that it was premature, given the lim- advancing national strategic initiatives that deal with specific challenges. The intention of this ited information available at the time, to base any decision about the Rus- service is to support professional development, sian’s intent, mission, or objectives. -
Summer 2002 PROFILES in FAITH in THIS ISSUE 1 Profiles in Faith: John Calvin (1509–1564) John Calvin by Art Lindsley by Dr
KKNOWINGNOWING A Teaching Quarterly for Discipleship of Heart and Mind C.S. LEWIS INSTITUTE OINGOING &D&D Summer 2002 PROFILES IN FAITH IN THIS ISSUE 1 Profiles in Faith: John Calvin (1509–1564) John Calvin by Art Lindsley by Dr. Art Lindsley Scholar-in-Residence 3 C.S. Lewis Feature Article: C.S. Lewis on Freud and Marx by Art Lindsley 6 A Conversation with: Ravi Zacharias 8 Review & Reflect: Two Giants and the he mere mention of John Calvin’s maintains, “Calvin is the man who, next to St. Giant Question: a name (born July 10, 1509 in Noyon, Paul, has done the most good to mankind.” review of Dr. France – died May 27, Charles Haddon Spurgeon, En- Armand Nicholi’s T book The Ques- 1564 in Geneva, Switzerland) glish preacher, asserts, “The T tion of God produces strong reactions both longer I live the clearer does it ap- by James Beavers pro and con. Erich Fromm, 20th “Taking into pear that John Calvin’s system is century German-born American the nearest to perfection.” 12 Special Feature psychoanalyst and social phi- account all his Basil Hall, Cambridge profes- Article: losopher, says that Calvin “be- sor, once wrote an essay, “The Conversational longed to the ranks of the failings, he Calvin Legend,” in which he ar- Apologetics greatest haters in history.” The gues that formerly those who by Michael must be Ramsden Oxford Dictionary of the Christian depreciated Calvin had at least Church maintains that Calvin reckoned as one read his works, whereas now 24 Upcoming Events was “cruel” and the “unopposed the word “Calvin” or “Calvin- dictator of Geneva.” On the other of the greatest ism” is used as a word with hand, Theodore Beza, Calvin’s negative connotations but with successor, says of Calvin, “I have and best of men little or no content. -
Quantifying Aristotle's Fallacies
mathematics Article Quantifying Aristotle’s Fallacies Evangelos Athanassopoulos 1,* and Michael Gr. Voskoglou 2 1 Independent Researcher, Giannakopoulou 39, 27300 Gastouni, Greece 2 Department of Applied Mathematics, Graduate Technological Educational Institute of Western Greece, 22334 Patras, Greece; [email protected] or [email protected] * Correspondence: [email protected] Received: 20 July 2020; Accepted: 18 August 2020; Published: 21 August 2020 Abstract: Fallacies are logically false statements which are often considered to be true. In the “Sophistical Refutations”, the last of his six works on Logic, Aristotle identified the first thirteen of today’s many known fallacies and divided them into linguistic and non-linguistic ones. A serious problem with fallacies is that, due to their bivalent texture, they can under certain conditions disorient the nonexpert. It is, therefore, very useful to quantify each fallacy by determining the “gravity” of its consequences. This is the target of the present work, where for historical and practical reasons—the fallacies are too many to deal with all of them—our attention is restricted to Aristotle’s fallacies only. However, the tools (Probability, Statistics and Fuzzy Logic) and the methods that we use for quantifying Aristotle’s fallacies could be also used for quantifying any other fallacy, which gives the required generality to our study. Keywords: logical fallacies; Aristotle’s fallacies; probability; statistical literacy; critical thinking; fuzzy logic (FL) 1. Introduction Fallacies are logically false statements that are often considered to be true. The first fallacies appeared in the literature simultaneously with the generation of Aristotle’s bivalent Logic. In the “Sophistical Refutations” (Sophistici Elenchi), the last chapter of the collection of his six works on logic—which was named by his followers, the Peripatetics, as “Organon” (Instrument)—the great ancient Greek philosopher identified thirteen fallacies and divided them in two categories, the linguistic and non-linguistic fallacies [1].