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skills/scientific-critical-thinking/references/logical_fallacies.md

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+# Logical Fallacies in Scientific Discourse
+
+## Fallacies of Causation
+
+### 1. Post Hoc Ergo Propter Hoc (After This, Therefore Because of This)
+**Description:** Assuming that because B happened after A, A caused B.
+
+**Examples:**
+- "I took this supplement and my cold went away, so the supplement cured my cold."
+- "Autism diagnoses increased after vaccine schedules changed, so vaccines cause autism."
+- "I wore my lucky socks and won the game, so the socks caused the win."
+
+**Why fallacious:** Temporal sequence is necessary but not sufficient for causation. Correlation ≠ causation.
+
+**Related:** *Cum hoc ergo propter hoc* (with this, therefore because of this) - correlation mistaken for causation even without temporal order.
+
+### 2. Confusing Correlation with Causation
+**Description:** Assuming correlation implies direct causal relationship.
+
+**Examples:**
+- "Countries that eat more chocolate have more Nobel Prize winners, so chocolate makes you smarter."
+- "Ice cream sales correlate with drowning deaths, so ice cream causes drowning."
+
+**Reality:** Often due to confounding variables (hot weather causes both ice cream sales and swimming).
+
+### 3. Reverse Causation
+**Description:** Confusing cause and effect direction.
+
+**Examples:**
+- "Depression is associated with inflammation, so inflammation causes depression." (Could be: depression causes inflammation)
+- "Wealthy people are healthier, so wealth causes health." (Could be: health enables wealth accumulation)
+
+**Solution:** Longitudinal studies and experimental designs to establish temporal order.
+
+### 4. Single Cause Fallacy
+**Description:** Attributing complex phenomena to one cause when multiple factors contribute.
+
+**Examples:**
+- "Crime is caused by poverty." (Ignores many other contributing factors)
+- "Heart disease is caused by fat intake." (Oversimplifies multifactorial disease)
+
+**Reality:** Most outcomes have multiple contributing causes.
+
+## Fallacies of Generalization
+
+### 5. Hasty Generalization
+**Description:** Drawing broad conclusions from insufficient evidence.
+
+**Examples:**
+- "My uncle smoked and lived to 90, so smoking isn't dangerous."
+- "This drug worked in 5 patients, so it's effective for everyone."
+- "I saw three black swans, so all swans are black."
+
+**Why fallacious:** Small, unrepresentative samples don't support universal claims.
+
+### 6. Anecdotal Fallacy
+**Description:** Using personal experience or isolated examples as proof.
+
+**Examples:**
+- "I know someone who survived cancer using alternative medicine, so it works."
+- "My grandmother never exercised and lived to 100, so exercise is unnecessary."
+
+**Why fallacious:** Anecdotes are unreliable due to selection bias, memory bias, and confounding. Plural of anecdote ≠ data.
+
+### 7. Cherry Picking (Suppressing Evidence)
+**Description:** Selecting only evidence that supports your position while ignoring contradictory evidence.
+
+**Examples:**
+- Citing only studies showing supplement benefits while ignoring null findings
+- Highlighting successful predictions while ignoring failed ones
+- Showing graphs that start at convenient points
+
+**Detection:** Look for systematic reviews, not individual studies.
+
+### 8. Ecological Fallacy
+**Description:** Inferring individual characteristics from group statistics.
+
+**Example:**
+- "Average income in this neighborhood is high, so this person must be wealthy."
+- "This country has low disease rates, so any individual from there is unlikely to have disease."
+
+**Why fallacious:** Group-level patterns don't necessarily apply to individuals.
+
+## Fallacies of Authority and Tradition
+
+### 9. Appeal to Authority (Argumentum ad Verecundiam)
+**Description:** Accepting claims because an authority figure said them, without evidence.
+
+**Examples:**
+- "Dr. X says this treatment works, so it must." (If Dr. X provides no data)
+- "Einstein believed in God, so God exists." (Einstein's physics expertise doesn't transfer)
+- "99% of doctors recommend..." (Appeal to majority + authority without evidence)
+
+**Valid use of authority:** Experts providing evidence-based consensus in their domain.
+
+**Invalid:** Authority opinions without evidence, or outside their expertise.
+
+### 10. Appeal to Antiquity/Tradition
+**Description:** Assuming something is true or good because it's old or traditional.
+
+**Examples:**
+- "Traditional medicine has been used for thousands of years, so it must work."
+- "This theory has been accepted for decades, so it must be correct."
+
+**Why fallacious:** Age doesn't determine validity. Many old beliefs have been disproven.
+
+### 11. Appeal to Novelty
+**Description:** Assuming something is better because it's new.
+
+**Examples:**
+- "This is the latest treatment, so it must be superior."
+- "New research overturns everything we knew." (Often overstated)
+
+**Why fallacious:** New ≠ better. Established treatments often outperform novel ones.
+
+## Fallacies of Relevance
+
+### 12. Ad Hominem (Attack the Person)
+**Description:** Attacking the person making the argument rather than the argument itself.
+
+**Types:**
+- **Abusive:** "He's an idiot, so his theory is wrong."
+- **Circumstantial:** "She's funded by industry, so her findings are false."
+- **Tu Quoque:** "You smoke, so your anti-smoking argument is invalid."
+
+**Why fallacious:** Personal characteristics don't determine argument validity.
+
+**Note:** Conflicts of interest are worth noting but don't invalidate evidence.
+
+### 13. Genetic Fallacy
+**Description:** Judging something based on its origin rather than its merits.
+
+**Examples:**
+- "This idea came from a drug company, so it's wrong."
+- "Ancient Greeks believed this, so it's outdated."
+
+**Better approach:** Evaluate evidence regardless of source.
+
+### 14. Appeal to Emotion
+**Description:** Manipulating emotions instead of presenting evidence.
+
+**Types:**
+- **Appeal to fear:** "If you don't vaccinate, your child will die."
+- **Appeal to pity:** "Think of the suffering patients who need this unproven treatment."
+- **Appeal to flattery:** "Smart people like you know that..."
+
+**Why fallacious:** Emotional reactions don't determine truth.
+
+### 15. Appeal to Consequences (Argumentum ad Consequentiam)
+**Description:** Arguing something is true/false based on whether consequences are desirable.
+
+**Examples:**
+- "Climate change can't be real because the solutions would hurt the economy."
+- "Free will must exist because without it, morality is impossible."
+
+**Why fallacious:** Reality is independent of what we wish were true.
+
+### 16. Appeal to Nature (Naturalistic Fallacy)
+**Description:** Assuming "natural" means good, safe, or effective.
+
+**Examples:**
+- "This treatment is natural, so it's safe."
+- "Organic food is natural, so it's healthier."
+- "Vaccines are unnatural, so they're harmful."
+
+**Why fallacious:**
+- Many natural things are deadly (arsenic, snake venom, hurricanes)
+- Many synthetic things are beneficial (antibiotics, vaccines)
+- "Natural" is often poorly defined
+
+### 17. Moralistic Fallacy
+**Description:** Assuming what ought to be true is true.
+
+**Examples:**
+- "There shouldn't be sex differences in ability, so they don't exist."
+- "People should be rational, so they are."
+
+**Why fallacious:** Desires about reality don't change reality.
+
+## Fallacies of Structure
+
+### 18. False Dichotomy (False Dilemma)
+**Description:** Presenting only two options when more exist.
+
+**Examples:**
+- "Either you're with us or against us."
+- "It's either genetic or environmental." (Usually both)
+- "Either the treatment works or it doesn't." (Ignores partial effects)
+
+**Reality:** Most issues have multiple options and shades of gray.
+
+### 19. Begging the Question (Circular Reasoning)
+**Description:** Assuming what you're trying to prove.
+
+**Examples:**
+- "This medicine works because it has healing properties." (What are healing properties? That it works!)
+- "God exists because the Bible says so, and the Bible is true because it's God's word."
+
+**Detection:** Check if the conclusion is hidden in the premises.
+
+### 20. Moving the Goalposts
+**Description:** Changing standards of evidence after initial standards are met.
+
+**Example:**
+- Skeptic: "Show me one study."
+- [Shows study]
+- Skeptic: "That's just one study; show me a meta-analysis."
+- [Shows meta-analysis]
+- Skeptic: "But meta-analyses have limitations..."
+
+**Why problematic:** No amount of evidence will ever be sufficient.
+
+### 21. Slippery Slope
+**Description:** Arguing that one step will inevitably lead to extreme outcomes without justification.
+
+**Example:**
+- "If we allow gene editing for disease, we'll end up with designer babies and eugenics."
+
+**When valid:** If intermediate steps are actually likely.
+
+**When fallacious:** If chain of events is speculative without evidence.
+
+### 22. Straw Man
+**Description:** Misrepresenting an argument to make it easier to attack.
+
+**Example:**
+- Position: "We should teach evolution in schools."
+- Straw man: "So you think we should tell kids they're just monkeys?"
+
+**Detection:** Ask: Is this really what they're claiming?
+
+## Fallacies of Statistical and Scientific Reasoning
+
+### 23. Texas Sharpshooter Fallacy
+**Description:** Cherry-picking data clusters to fit a pattern, like shooting arrows then drawing targets around them.
+
+**Examples:**
+- Finding cancer clusters and claiming environmental causes (without accounting for random clustering)
+- Data mining until finding significant correlations
+
+**Why fallacious:** Patterns in random data are inevitable; finding them doesn't prove causation.
+
+### 24. Base Rate Fallacy
+**Description:** Ignoring prior probability when evaluating evidence.
+
+**Example:**
+- Disease affects 0.1% of population; test is 99% accurate
+- Positive test ≠ 99% probability of disease
+- Actually ~9% probability (due to false positives exceeding true positives)
+
+**Solution:** Use Bayesian reasoning; consider base rates.
+
+### 25. Prosecutor's Fallacy
+**Description:** Confusing P(Evidence|Innocent) with P(Innocent|Evidence).
+
+**Example:**
+- "The probability of this DNA match occurring by chance is 1 in 1 million, so there's only a 1 in 1 million chance the defendant is innocent."
+
+**Why fallacious:** Ignores base rates and prior probability.
+
+### 26. McNamara Fallacy (Quantitative Fallacy)
+**Description:** Focusing only on what can be easily measured while ignoring important unmeasured factors.
+
+**Example:**
+- Judging school quality only by test scores (ignoring creativity, social skills, ethics)
+- Measuring healthcare only by quantifiable outcomes (ignoring quality of life)
+
+**Quote:** "Not everything that counts can be counted, and not everything that can be counted counts."
+
+### 27. Multiple Comparisons Fallacy
+**Description:** Not accounting for increased false positive rate when testing many hypotheses.
+
+**Example:**
+- Testing 20 hypotheses at p < .05 gives ~65% chance of at least one false positive
+- Claiming jellybean color X causes acne after testing 20 colors
+
+**Solution:** Correct for multiple comparisons (Bonferroni, FDR).
+
+### 28. Reification (Hypostatization)
+**Description:** Treating abstract concepts as if they were concrete things.
+
+**Examples:**
+- "Evolution wants organisms to survive." (Evolution doesn't "want")
+- "The gene for intelligence" (Intelligence isn't one gene)
+- "Nature selects..." (Nature doesn't consciously select)
+
+**Why problematic:** Can lead to confused thinking about mechanisms.
+
+## Fallacies of Scope and Definition
+
+### 29. No True Scotsman
+**Description:** Retroactively excluding counterexamples by redefining criteria.
+
+**Example:**
+- "No natural remedy has side effects."
+- "But poison ivy is natural and causes reactions."
+- "Well, no *true* natural remedy has side effects."
+
+**Why fallacious:** Moves goalposts to protect claim from falsification.
+
+### 30. Equivocation
+**Description:** Using a word with multiple meanings inconsistently.
+
+**Example:**
+- "Evolution is just a theory. Theories are guesses. So evolution is just a guess."
+- (Conflates colloquial "theory" with scientific "theory")
+
+**Detection:** Check if key terms are used consistently.
+
+### 31. Ambiguity
+**Description:** Using vague language that can be interpreted multiple ways.
+
+**Example:**
+- "Quantum healing" (What does "quantum" mean here?)
+- "Natural" (Animals? Not synthetic? Organic? Common?)
+
+**Why problematic:** Claims become unfalsifiable when terms are undefined.
+
+### 32. Mind Projection Fallacy
+**Description:** Projecting mental constructs onto reality.
+
+**Example:**
+- Assuming categories that exist in language exist in nature
+- "Which chromosome is the gene for X on?" when X is polygenic and partially environmental
+
+**Better:** Recognize human categories may not carve nature at the joints.
+
+## Fallacies Specific to Science
+
+### 33. Galileo Gambit
+**Description:** "They laughed at Galileo, and he was right, so if they're laughing at me, I must be right too."
+
+**Why fallacious:**
+- They laughed at Galileo, and he was right
+- They also laughed at countless crackpots who were wrong
+- Being an outsider doesn't make you right
+
+**Reality:** Revolutionary ideas are usually well-supported by evidence.
+
+### 34. Argument from Ignorance (Ad Ignorantiam)
+**Description:** Assuming something is true because it hasn't been proven false (or vice versa).
+
+**Examples:**
+- "No one has proven homeopathy doesn't work, so it works."
+- "We haven't found evidence of harm, so it must be safe."
+
+**Why fallacious:** Absence of evidence ≠ evidence of absence (though it can be, depending on how hard we've looked).
+
+**Burden of proof:** Falls on the claimant, not the skeptic.
+
+### 35. God of the Gaps
+**Description:** Explaining gaps in knowledge by invoking supernatural or unfalsifiable causes.
+
+**Examples:**
+- "We don't fully understand consciousness, so it must be spiritual."
+- "This complexity couldn't arise naturally, so it must be designed."
+
+**Why problematic:**
+- Fills gaps with non-explanations
+- Discourages genuine investigation
+- History shows gaps get filled by natural explanations
+
+### 36. Nirvana Fallacy (Perfect Solution Fallacy)
+**Description:** Rejecting solutions because they're imperfect.
+
+**Examples:**
+- "Vaccines aren't 100% effective, so they're worthless."
+- "This diet doesn't work for everyone, so it doesn't work."
+
+**Reality:** Most interventions are partial; perfection is rare.
+
+**Better:** Compare to alternatives, not to perfection.
+
+### 37. Special Pleading
+**Description:** Applying standards to others but not to oneself.
+
+**Examples:**
+- "My anecdotes count as evidence, but yours don't."
+- "Mainstream medicine needs RCTs, but my alternative doesn't."
+- "Correlation doesn't imply causation—except when it supports my view."
+
+**Why fallacious:** Evidence standards should apply consistently.
+
+### 38. Unfalsifiability
+**Description:** Formulating claims in ways that cannot be tested or disproven.
+
+**Examples:**
+- "This energy can't be detected by any instrument."
+- "It works, but only if you truly believe."
+- "Failures prove the conspiracy is even deeper."
+
+**Why problematic:** Unfalsifiable claims aren't scientific; they can't be tested.
+
+**Good science:** Makes specific, testable predictions.
+
+### 39. Affirming the Consequent
+**Description:** If A, then B. B is true. Therefore, A is true.
+
+**Example:**
+- "If the drug works, symptoms improve. Symptoms improved. Therefore, the drug worked."
+- (Could be placebo, natural history, regression to mean)
+
+**Why fallacious:** Other causes could produce the same outcome.
+
+**Valid form:** Modus ponens: If A, then B. A is true. Therefore, B is true.
+
+### 40. Denying the Antecedent
+**Description:** If A, then B. A is false. Therefore, B is false.
+
+**Example:**
+- "If you have fever, you have infection. You don't have fever. Therefore, you don't have infection."
+
+**Why fallacious:** B can be true even when A is false.
+
+## Avoiding Logical Fallacies
+
+### Practical Steps
+
+1. **Identify the claim** - What exactly is being argued?
+
+2. **Identify the evidence** - What supports the claim?
+
+3. **Check the logic** - Does the evidence actually support the claim?
+
+4. **Look for hidden assumptions** - What unstated beliefs does the argument rely on?
+
+5. **Consider alternatives** - What other explanations fit the evidence?
+
+6. **Check for emotional manipulation** - Is the argument relying on feelings rather than facts?
+
+7. **Evaluate the source** - Are there conflicts of interest? Is this within their expertise?
+
+8. **Look for balance** - Are counterarguments addressed fairly?
+
+9. **Assess the evidence** - Is it anecdotal, observational, or experimental? How strong?
+
+10. **Be charitable** - Interpret arguments in their strongest form (steel man, not straw man).
+
+### Questions to Ask
+
+- Is the conclusion supported by the premises?
+- Are there unstated assumptions?
+- Is the evidence relevant to the conclusion?
+- Are counterarguments acknowledged?
+- Could alternative explanations account for the evidence?
+- Is the reasoning consistent?
+- Are terms defined clearly?
+- Is evidence being cherry-picked?
+- Are emotions being manipulated?
+- Would this reasoning apply consistently to other cases?
+
+### Common Patterns
+
+**Good Arguments:**
+- Clearly defined terms
+- Relevant, sufficient evidence
+- Valid logical structure
+- Acknowledges limitations and alternatives
+- Proportional conclusions
+- Transparent about uncertainty
+- Applies consistent standards
+
+**Poor Arguments:**
+- Vague or shifting definitions
+- Irrelevant or insufficient evidence
+- Logical leaps
+- Ignores counterevidence
+- Overclaimed conclusions
+- False certainty
+- Double standards
+
+## Remember
+
+- **Fallacious reasoning doesn't mean the conclusion is false** - just that this argument doesn't support it.
+- **Identifying fallacies isn't about winning** - it's about better understanding reality.
+- **We all commit fallacies** - recognizing them in ourselves is as important as in others.
+- **Charity principle** - Interpret arguments generously; don't assume bad faith.
+- **Focus on claims, not people** - Ad hominem goes both ways.