Class Ten: Argument: Rules

September 27, 2012

INTRODUCTION TO ADOPTED RULES

An adopted rule is a principle used to ascertain the truth about a matter.  Every rule claims to identify a meaningful relationship - or absence of a meaningful relationship - between an “A” and a “B.”  Almost every single argument Every opinion assumes, incorporates, applies an adopted rule to the determined facts.  As discussed before, particularly with complex arguments, the End-Point-Conclusions require the application of several rules to support a chain of Supporting Conclusions.

When analyzing rules it is important to keep in mind three aspects of rules: (1) The Type of the Rule; (2) The Source of the Rule (Methodology); (3) The Acceptance of the Rule; and (4) the Confidence Rate of the Rule.

There are nine types of Rules:

1. Correlation Rule - If A then B.
2. Causation Rule - A causes B, or the reverse, A does not cause B.
3. Definition Rule - A clearly defined set of factors which if established must necessarily prove the assertion.  Example:  A Square or Rectangle must have 90 degree angles.
4. Probability Rule - Also known as “Probably-a-Duck” Rule.  Frequently there is no neat rule that is based on a standard, formula, definition, generalization, statistic, causal relationship, mutual “exclusivity” … usually because the potentially relevant variables are many and the set of “known” variables, case-by-case, is unique; thus this common-sense rule is utilized.  So long as a majority of relatively equally important factors supports the same opinion, then that opinion is probably correct … so long as no factor that is absolutely contrary to that opinion is established.
5. Standards Rule - A directive or prohibition imposed by a government body or adopted by a specialty group.  For example, Per State Statute, vehicles traveling in school zones shall not exceed 20 mph; or (2) The standard of care requires all that Doctors not have intimate relations with their patients.
6. Formula Rule - A equation for which all the potential variables have been identified and the interrelationship of each variable has been determined.  In other words, one need only plug the data into the appropriate places and perform the calculation to discover the value of the relevant unknown variable in the instant case.  Example: To determine the area of a circle you use πR2.
7. Statistic Rule - The Data supports the ability to assign a numerical probability that the assertion is true.
8. Value System Rule - Where two “good” values are in conflict with each other, requiring a value judgement as to which should predominate.  FOR EXAMPLE:  (1) Safety vs. Cost; (2) Individual vs. Group; (3) Exactitude vs. Efficiency; (4) Principle vs. Pragmatism; (5) Aesthetics vs. Function; (6) Candor vs. Diplomacy.
9. Generalization Rule - Everybody knows the assertion to be true without resort to specific specialized knowledge or experience.  Example:  People typically don’t buy moldy food.

Many of these are adopted from Robert Mussante’s Excellent “Deposing the Adverse Expert” Legal Education Course.

http://www.killerdepo.com/opinion.html

Sources (Methodology) of Rules

There are three sources for rules: (1) The Expert Source; (2) The Experiential Source; and (3) The Non-Expert Source.

Expert Source

The rule has come from other individuals or external sources such as:  (1) Authoritative Texts; (2) Corroboration that rule is shared by other experts: (3) Expert of renown; (4) scientific study; (5) Educational Institute; (6) Governmental Group; or (7) Commercial group.

The Experiential Source

The rule comes from the speaker’s own presumably vast, varied and exhaustive experience in the field.  The experience is unique and the result of specialized study, work, or other endeavor.

The Non-Expert Source

The rule comes from the speaker’s own experience, however that experience is no different than the average lay person.

Acceptance of the Rule

As with facts, almost all rules are not universally accepted to be correct and complete.  Therefore it is important to understand how widely adopted the rule is in analyzing the argument.  These fall into six levels:

1. Universally Adopted.  The rule is accepted and identified by the entire relevant community.  No other alternative rules exist that are worthy of consideration.
2. Overwhelmingly Adopted.  The rule is accepted by a vast majority (75% or more) of the relevant community.  While other alternatives exist and are worthy of consideration, only a small percentage prefer that rule over the accepted one.  Also the accepted rule may have flaws or “holes” that fail in certain discrete and rare situations.
3. Majority Adopted.  The rule is accepted by more than 50% of the relevant community however other plausible and possible alternative rules exist.  Further the accepted rule may still be in development, or be shown to be inadequate in several areas.
4. Plurality Adopted.  The rule is adopted by most, but not a majority, of the relevant community.  Other alternative rules exist that are worthy of consideration.  The plurality rule still must defend its validity and superiority over other alternatives.
5. Minority Rule.  This rule is  adopted by less than a plurality of the relevant community.  The rule may have been the previous “gold standard” but because of new developments, has fallen into disfavor.  Or new developments may have led to the creation of the minority rule.  This rule is still worthy of consideration.
6. Improbable and unworthy of Consideration.  This rule has been discredited sufficiently as to me unworthy of consideration.

Confidence Rate of the Rule

Only a minority of rules are correct all of the time.  When rules are used to determine the existence or non-existence of a thing, for example, does the person have a disease, it is critical to know the Confidence Rate.  A rule’s Confidence Rate will affect its reliability and acceptance.  Another term that is used is the Error Rate.  An error rate of a rule can be mathematically calculated given the following inputs:

TRUE POSITIVE RATE - The odds that the rule will correctly determine that the thing exists.

FALSE POSITIVE RATE - The odds that the rule will incorrectly determine that the thing exists when, in fact, it does not.

TRUE NEGATE RATE - The odds that the rule correctly determine the absence of the thing.

FALSE NEGATIVE RATE - The odds that the rule will incorrectly determine that thing does not exist when, in fact, it does.