scholarly journals Sensitivity of implicit evaluations to accurate and erroneous propositional inferences

2021 ◽  
Author(s):  
Benedek Kurdi ◽  
Yarrow Dunham
Keyword(s):  
Bayesian Modeling ◽  
Logical Structure ◽  
Modus Ponens ◽  
Learning Phase ◽  
Self Report ◽  
Conditional Statements ◽  
Novel Targets ◽  
Truth Value ◽  
Competing Ideas ◽  
Affirming The Consequent

Explicit (directly measured) evaluations are widely assumed to be sensitive to logical structure. However, whether implicit (indirectly measured) evaluations are uniquely sensitive to co-occurrence information or can also reflect logical structure has been a matter of theoretical debate. To test these competing ideas, participants (N = 3,928) completed a learning phase consisting of a series of two-step trials. In step 1, one or more conditional statements (A → B) containing novel targets co-occurring with valenced adjectives (e.g., “if you see a blue square, Ibbonif is sincere”) were presented. In step 2, a disambiguating stimulus, e.g., blue square (A) or gray blob (¬A) was revealed. Co-occurrence information, disambiguating stimuli, or both were varied between conditions to enable investigating the unique and joint effects of each. Across studies, the combination of conditional statements and disambiguating stimuli licensed different normatively accurate inferences. In Study 1, participants were prompted to use modus ponens (inferring B from A → B and A). In Studies 2–4, the information did not license accurate inferences, but some participants made inferential errors: affirming the consequent (inferring A from A → B and B; Study 2) or denying the antecedent (inferring ¬B from A → B and ¬A; Studies 3A, 3B, and 4). Bayesian modeling using ordinal constraints on condition means yielded consistent evidence for the sensitivity of both explicit (self-report) and implicit (IAT and AMP) evaluations to the (correctly or erroneously) inferred truth value of propositions. Together, these data suggest that implicit evaluations, similar to their explicit counterparts, can reflect logical structure.

scholarly journals Sensitivity of implicit evaluations to accurate and erroneous propositional inferences

2021 ◽  
Author(s):  
Benedek Kurdi ◽  
Yarrow Dunham
Keyword(s):  
Bayesian Modeling ◽  
Logical Structure ◽  
Modus Ponens ◽  
Learning Phase ◽  
Self Report ◽  
Conditional Statements ◽  
Novel Targets ◽  
Truth Value ◽  
Competing Ideas ◽  
Affirming The Consequent

Explicit (directly measured) evaluations are widely assumed to be sensitive to logical structure. However, whether implicit (indirectly measured) evaluations are uniquely sensitive to co-occurrence information or can also reflect logical structure has been a matter of theoretical debate. To test these competing ideas, participants (N = 3,928) completed a learning phase consisting of a series of two-step trials. In step 1, one or more conditional statements (A → B) containing novel targets co-occurring with valenced adjectives (e.g., “if you see a blue square, Ibbonif is sincere”) were presented. In step 2, a disambiguating stimulus, e.g., blue square (A) or gray blob (¬A) was revealed. Co-occurrence information, disambiguating stimuli, or both were varied between conditions to enable investigating the unique and joint effects of each. Across studies, the combination of conditional statements and disambiguating stimuli licensed different normatively accurate inferences. In Study 1, participants were prompted to use modus ponens (inferring B from A → B and A). In Studies 2–4, the information did not license accurate inferences, but some participants made inferential errors: affirming the consequent (inferring A from A → B and B; Study 2) or denying the antecedent (inferring ¬B from A → B and ¬A; Studies 3A, 3B, and 4). Bayesian modeling using ordinal constraints on condition means yielded consistent evidence for the sensitivity of both explicit (self-report) and implicit (IAT and AMP) evaluations to the (correctly or erroneously) inferred truth value of propositions. Together, these data suggest that implicit evaluations, similar to their explicit counterparts, can reflect logical structure.

Modus Ponens, Modus Tollens, and Likeness

1998 ◽  
pp. 45-52
Author(s):  
Mustafa M. Dagli
Keyword(s):  
Modus Ponens ◽  
General Idea ◽  
Modus Tollens ◽  
Ordinary Life ◽  
Conditional Statements ◽  
Reasoning Patterns ◽  
Actual Life

Modus Ponens (MP) and Modus Tollens (MT) are taught as basic rules of inference related to conditional statements in introductory logic courses. In ordinary reasoning, MP and MT can have important roles in modes of argumentation. However, one can also distinguish counter-examples to such reasoning patterns when considered as ‘strictly’ valid rules (i.e., McGee’s counterattacks for MP, and Adams’ criticisms of MT). I suggest that this problem can be resolved if we revise MP and MT as basic tools of logic, assuming the above-mentioned counter-cases are valid, on the basis of nonmonotonicity. If the only thing that we know is ‘Tweety is a bird,’ we say ‘Tweety flies.’ But, after learning ‘Tweety is an ostrich,’ we (change our minds and) say, ‘Tweety does not fly.’ In actual life, we use ‘rules of logic’ in a limited sense; when we learn new facts, we change some of our beliefs sometimes. The question arises, ‘In which situation, which exception does not violate which rule?’ When reasoning about something, we use some semantic patterns in order to make inferences, or for the sake of argumentation. Two reasoning patterns employed in ordinary life scenes concerning conditional statements will be identified as MP-like and MT-like. These will be exemplified and discussed. The general idea guiding this tableau will be stated as likeness.

scholarly journals Logical Intuition Is Not Really About Logic

2021 ◽  
Author(s):  
Omid Ghasemi ◽  
Simon Handley ◽  
Stephanie Howarth ◽  
Ian Randal Newman ◽  
Valerie A Thompson
Keyword(s):  
Structural Feature ◽  
Modus Ponens ◽  
Structural Features ◽  
Modus Tollens ◽  
Logical Validity ◽  
Affirming The Consequent

Recent research suggest that reasoners are able to draw simple logical or probabilistic inferences relatively intuitively and automatically, a capacity which has been termed “logical intuition” (see, for example, De Neys & Pennycook, 2019). A key finding in support of this interpretation is that conclusion validity consistently interferes with judgments of conclusion believability, suggesting that information about logical validity is available quickly enough to interfere with belief judgments. In this paper we examined whether logical intuitions arise because reasoners are sensitive to the logical features of problem or another structural feature that just happens to aligns with logical validity. In three experiments (N = 113, 137, and 122), we presented participants with logical (determinate) and pseudo-logical (indeterminate) arguments and asked them to judge the validity or believability of the conclusion. Logical arguments had determinately valid or invalid conclusions, whereas pseudo-logical arguments were all logically indeterminate, but some were pseudo-valid (possible ‘strong’ arguments) and others pseudo-invalid (possible ‘weak’ arguments). Experiments 1 and 2 used simple Modus Ponens and Affirming the Consequent structures; Experiment 3 used more complex Denying the Antecedent and Modus Tollens structures. In all three experiments, we found that pseudo-validity interfered with belief judgments to the same extent as real validity. Altogether, these findings suggest that whilst people are able to draw inferences intuitively, and these inferences impact on belief judgments, they are not ‘logical intuitions.’ Rather, the intuitive inferences are driven by the processing of more superficial structural features that happen to align with logical validity.

Conditionals, Inference, and Possibility in Ancient Mesopotamian Science

2009 ◽  
Vol 22 (1) ◽  
pp. 5-25 ◽  
Author(s):  
Francesca Rochberg
Keyword(s):  
Scientific Knowledge ◽  
Institutional Context ◽  
Logical Structure ◽  
Epistemic Possibility ◽  
Inferential Reasoning ◽  
Conditional Statements ◽  
Cognitive Disposition ◽  
Physical Phenomena

ArgumentThis paper argues that ancient Babylonian signs (omens) reflect a mode of inferential reasoning as a function of their syntactic and logical structure as conditionals. Taking into account the institutional context that produced a systematic written body of omens, the paper is principally interested in the cognitive disposition of such texts. Investigating what constitutes system in these works, formal aspects of the material are examined in terms of the nature of conditionals and the logic of conditional statements. It is argued that conditional statements about ominous phenomena speak as much to a notion of conceivability and possibility as to empirical physical actuality. It is claimed that the epistemological character of the Babylonian compendia of signs cannot be understood without due attention to epistemic possibility and further, that the cuneiform omen texts comprise a different kind of scientific knowledge from that limited to a knowledge of physical phenomena and their laws.

Bias in Conditional Inference: Implications for Mental Models and Mental Logic

1995 ◽  
Vol 48 (3) ◽  
pp. 644-670 ◽  
Author(s):  
Jonathan St.B.T. Evans ◽  
John Clibbens ◽  
Benjamin Rood
Keyword(s):  
Mental Model ◽  
Modus Ponens ◽  
Conditional Inference ◽  
Modus Tollens ◽  
Production Task ◽  
Double Negation ◽  
Evaluation Task ◽  
Conditional Statements ◽  
Negative Conclusion ◽  
Mental Logic

Three experiments are reported in which subjects are given the opportunity to make any of the four inferences associated with conditional statements: modus ponens (MP), denial of the antecedent (DA), affirmation of the consequent (AC), and modus tollens (MT). The primary purpose of the research was to establish the generality and robustness of polarity biases that may be occasioned by systematic rotation of negative components in the conditional rules. In Experiments 1 & 2, three forms of conditionals were used: “if (not) p then (not) q”, “(not) p only if (not) q” and “(not) q if (not) p”. Experiment 1 used a conclusion evaluation task, whereas Experiment 2 used a conclusion production task. In Experiment 3, thematic conditionals were presented with and without a preceding scenario. The biases investigated were (a) affirmative premise bias—the tendency to draw more inferences from affirmative premises and (b) negative conclusion bias—the tendency to draw more inferences with negative conclusions. The suggestive evidence for affirmative premise bias in the literature was not supported: very little evidence was found for it in the current experiments. Robust findings of negative conclusion bias were, however, found across the three experiments, although the bias was mostly restricted to DA and MT inferences. This suggests that the bias is best regarded as a difficulty with double negation. The results are discussed with respect to both the mental logic and mental model accounts of propositional reasoning. Neither theory as currently formulated can explain all of our findings, although a plausible revision of each is considered.

scholarly journals Basic Contradiction in Religion

2018 ◽  
Vol 2 (1) ◽  
pp. 31-38
Author(s):  
Nabil Nabil
Keyword(s):  
Logical Structure ◽  
Truth Table ◽  
False Statement ◽  
Logical Language ◽  
Fundamental Law ◽  
Truth Value ◽  
The Law ◽  
Unity Of Opposites

Contradiction provide insights into theoritical changes in perspective that lead to multi interpretation the law of contradiction contained unity of opposites in the religion is a fundamental law. And it turns out that there are contradiction in the basic religion of islam, namely syahadat as Ahmad Yulden Erwin in his writing, the contradiction are true and empty is the content.“No god but God” if the phrase is to be written in symbolic logical language, it will be form into contradiction of proposition; -p ᴧ p (which has wrong value). If the phrase is to be written in mathematic language, it will be form; -1 + 1 (which value 0). In other words, “syahadat” is a testimony of contradiction and emptiness. Accordingly the meaning, the phrase on a symbolically logical structure will be value wrong and or empty, except , if and if only. Logic can already prove that the contradiction are true and empty it was none other than content.Contradiction is the opposite of tautology, which is a form of statement that has only an example of a wrong substance, or a false statement in everything regardless of truth value of it’s components.[1] To prove whether a statement is a contradiction, there are two ways to prove it. First is using a truth table, if all the options are F or false then they are called contradictions. The truth table of [( p⟹  q ) ˄ p] ˄ ~q 

scholarly journals Supposition, Conditionals and Unstated Premises

1992 ◽  
Vol 14 (2) ◽  
Author(s):  
E.P. Brandon
Keyword(s):  
Modus Ponens ◽  
Modus Tollens ◽  
Frequent Use ◽  
Conditional Statements

Informal logicians recognise the frequent use of unstated assumptions; some (e.g. Fisher) also recognise entertained arguments and recommend a suppositional approach (such as Mackie's) to conditional statements. It is here argued that these two be put together to make argument diagrams more accurate and subtle. Philosophical benefits also accrue: insights into Jackson's apparent violations of modus tollens and contraposition and McGee's counterexamples to the validity of modus ponens.

scholarly journals Reconditioning the conditional [Recondicionando o condicional]

2016 ◽  
Vol 23 (40) ◽  
pp. 9-27
Author(s):  
David Miller
Keyword(s):  
Conditional Probability ◽  
Probability Function ◽  
Primary Concern ◽  
Conditional Probabilities ◽  
Indicative Conditional ◽  
Everyday Language ◽  
Conditional Statements ◽  
The Absolute ◽  
Truth Value

Many authors have hoped to understand the indicative conditional construction in everyday language by means of what are usually called conditional probabilities. Other authors have hoped to make sense of conditional probabilities in terms of the absolute probabilities of conditional statements. Although all such hopes were disappointed by the triviality theorems of Lewis (1976), there have been copious subsequent attempts both to rescue CCCP (the conditional construal of conditional probability) and to extend and to intensify the arguments against it. In this paper it will be shown that triviality is avoidable if the probability function is replaced by an alternative generalization of the deducibility relation, the measure of deductive dependence of Miller and Popper (1986). It will be suggested further that this alternative way of orchestrating conditionals is nicely in harmony with the test proposed in Ramsey (1931), and also with the idea that it is not the truth value of a conditionalstatement that is of primary concern but its assertability or acceptability.

Perspectives of Fuzzy Logic and Their Applications

2021 ◽  
Vol 2 (1) ◽  
pp. 99-145
Author(s):  
Shivlal Mewada
Keyword(s):  
Applied Sciences ◽  
Fuzzy Logic ◽  
Fuzzy Numbers ◽  
Fuzzy Inference ◽  
Fuzzy Variable ◽  
Modus Ponens ◽  
Knowledge Based ◽  
Base Variable ◽  
Truth Value ◽  
Hypothetical Syllogism

Fuzzy logic is a highly suitable and applicable basis for developing knowledge-based systems in engineering and applied sciences. The concepts of a fuzzy number plays a fundamental role in formulating quantitative fuzzy variable. These are variable whose states are fuzzy numbers. When in addition, the fuzzy numbers represent linguistic concepts, such as very small, small, medium, and so on, as interpreted in a particular contest, the resulting constructs are usually called linguistic variables. Each linguistic variable the states of which are expressed by linguistic terms interpreted as specific fuzzy numbers is defined in terms of a base variable, the value of which are real numbers within a specific range. A base variable is variable in the classical sense, exemplified by the physical variable (e.g., temperature, pressure, speed, voltage, humidity, etc.) as well as any other numerical variable (e.g., age, interest rate, performance, salary, blood count, probability, reliability, etc.). Logic is the science of reasoning. Symbolic or mathematical logic is a powerful computational paradigm. Just as crisp sets survive on a 2-state membership (0/1) and fuzzy sets on a multistage membership [0 - 1], crisp logic is built on a 2-state truth-value (true or false) and fuzzy logic on a multistage truth-value (true, false, very true, partly false and so on). The author now briefly discusses the crisp logic and fuzzy logic. The aim of this paper is to explain the concept of classical logic, fuzzy logic, fuzzy connectives, fuzzy inference, fuzzy predicate, modifier inference from conditional fuzzy propositions, generalized modus ponens, generalization of hypothetical syllogism, conditional, and qualified propositions. Suitable examples are given to understand the topics in brief.

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