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Classism

Also Known As: Class Discrimination Socioeconomic Bias Poverty Shaming Elitism Snobbery
Manipulation & Propaganda 🎯 Discrimination Detection ID: classism

Definition

Classism encompasses language patterns that demean, stereotype, or marginalize people based on their socioeconomic status. It includes poverty shaming ('if they just worked harder'), meritocracy myths ('anyone can make it if they try'), cultural elitism (mocking accents, education levels, or consumption patterns of lower-income groups), and 'welfare queen' narratives that frame poverty as a moral failing rather than a structural condition. Classism operates in both directions: lower classes are stereotyped as lazy or uneducated, while wealthy individuals may face the assumption that their success is unearned — though this 'upward classism' rarely carries the same structural consequences.

Examples

A pundit argues: 'People on welfare simply lack the motivation to improve their situation. In this country, anyone who works hard enough can succeed.'

A social media influencer mocks someone's discount-store clothing: 'Imagine shopping there unironically — some people just have no standards.' This equates economic constraint with lack of taste or worth.

A politician proposes drug testing for welfare recipients, stating: 'We need to make sure taxpayer money isn't funding bad habits,' implicitly framing poverty as linked to substance abuse.

Formal Logic Pattern
FOL Pattern
The First-Order Logic formula representing this reasoning pattern's logical structure.
FOL (First-Order Logic) uses quantifiers (∀ = for all, ∃ = there exists), connectives (∧ = and, ∨ = or, ⇒ = implies, ¬ = not), and predicates to capture the essential form of a reasoning pattern. For example, the Ad Hominem fallacy: Person(x) ∧ HasFlaw(x) ⇒ Invalid(Claim(x)). These patterns allow automated verification of logical validity.

∃c∃p(SocioeconomicClass(c) ∧ Property(p) ∧ ∀x(InClass(x,c) → Attributed(x,p)) ∧ Devaluing(p))
Formal Verification:
Formal Verification
Checks whether a reasoning pattern is logically valid or invalid using an automated theorem prover.
Formal verification uses an SMT (Satisfiability Modulo Theories) solver — specifically Z3 — to mathematically check whether an argument's logical structure is valid. Each reasoning pattern is translated into First-Order Logic and tested: Can the premises be true while the conclusion is false? If yes, it's formally invalid. If no, it's formally valid. Many real-world patterns (analogies, heuristics) cannot be fully captured in formal logic — these are marked as not formally decidable, which doesn't mean they're wrong.
Not formally decidable

Verification Steps
Verification Steps
Binary yes/no questions that an AI must answer to detect a reasoning pattern in a text.
Each of the 452 aspects has verification steps — simple yes/no questions designed to systematically detect whether a pattern appears in a text. For ad hominem: "Does the argument attack a person rather than their claim?" For false dichotomy: "Are only two options presented when more exist?" This ensures consistent, reproducible analysis.

Binary (yes/no) questions an LLM must answer to identify this aspect:

  1. 1

    Does the statement demean, stereotype, or devalue people based on their socioeconomic status?

    Type: binary
  2. 2

    Does it imply that economic position reflects personal merit or moral character?

    Type: binary
  3. 3

    Does the framing ignore structural factors that contribute to socioeconomic inequality?

    Type: binary
  4. 4

    Does the language shame poverty or glorify wealth as inherently virtuous?

    Type: binary
Deep Dive
The expandable detail section on each aspect page with examples, psychology, and counter-strategies.
The Deep Dive section provides in-depth information about each aspect: a real-world example showing the pattern in action, an explanation of why it works psychologically, practical advice on how to counter it, alternative names, and links to related aspects.