State Law—Uniform Alcoholism and Intoxication Treatment Act, Wash. Rev. Code ch. 70.96A (1974)—Decriminalization of Alcoholism—Alcoholism as a Defense to Criminal Liability

On January 1, 1975, the Washington State Uniform Alcoholism and Intoxication Treatment Act (the Act) became effective. It directs that treatment replace punishment as the appropriate mechanism for dealing with alcoholics and intoxicated persons. The Act repeals or amends all criminal law provisions relating to public drunkenness and mandates a comprehensive treatment program for persons with alcohol problems. This note examines the mechanics of the Washington Act and the legislative determination that alcoholism is a disease and that the drinking it induces is beyond the control of the alcoholic. Consideration is given to whether Washington law can consistently treat chronic alcoholism as a disease for purposes of dealing with the public inebriate while continuing to hold that the intoxication of an alcoholic is a voluntary condition for purposes of criminal prosecution. Finally, a rule is formulated to accommodate both the disease concept of alcoholism and principles of criminal culpability

Arguings and arguments

Includes bibliographical references (page 27)

Categoricity of partial logics

Includes bibliographical references (page 202)

Syllogisms with fractional quantifiers

Includes bibliographical references (page 422).Aristotle's syllogistic is extended to include denumerably many quantifiers such as more than 2/3' and exactly 2/3'. Syntactic and semantic decision procedures determine the validity, or invalidity, of syllogisms with any finite number of premises. One of the syntactic procedures uses a natural deduction account of deducibility, which is sound and complete. The semantics for the system is non-classical since sentences may be assigned a value other than true or false. Results about symmetric systems are given. And reasons are given for claiming that syllogistic validity is relevant validity

Three-valued interpretation for a relevance logic, A

In this paper an entailment relation which holds between certain propositions of the propositional calculus will be defined both syntactically and semantically. Some theorems about this relation will show why one could not follow Lewis to prove that a contradiction entails, for the notion of entailment discussed below, every proposition

Analogical arguings and explainings

Includes bibliographical references (page 160).Johnson takes arguings and explainings to be more fundamental than arguments and explanations. The former require agents for their explication. Johnson contends that the texts fail to recognize that many ordinary analogical arguments and explanations have a deductive structure. According to Johnson, analogies are often used to state general principles, which are a part of the structure of analogical arguments and explanations. Johnson compares his analysis of analogies with Levi's analysis of legal reasoning and with Aristotle's analysis of "reasoning by example."Publisher version: http://ojs.uwindsor.ca/ojs/leddy/index.php/informal_logic/article/view/2629/2070

Categorical consequence for paraconsistent logic

Includes bibliographical references (pages 149-150).Consequence relations over sets of "judgments" are defined by using "overdetermined" as well as "underdetermined" valuations. Some of these relations are shown to be categorical. And generalized soundness and completeness results are given for both multiple and single conclusion categorical consequence relations

Conditions and Limitations on Learning in the Adaptive Management of Mallard Harvests

In 1995, the United States Fish and Wildlife Service adopted a protocol for the adaptive management of waterfowl hunting regulations (AHM) to help reduce uncertainty about the magnitude of sustainable harvests. To date, the AHM process has focused principally on the midcontinent population of mallards (Anas platyrhynchos), whose dynamics are described by 4 alternative models. Collectively, these models express uncertainty (or disagreement) about whether harvest is an additive or a compensatory form of mortality and whether the reproductive process is weakly or strongly density-dependent. Each model is associated with a probability or weight, which describes its relative ability to predict changes in population size. These Bayesian probabilities are updated annually using a comparison of population size predicted under each model with that observed by a monitoring program. The current AHM process is passively adaptive, in the sense that there is no a priori consideration of how harvest decisions might affect discrimination among models. We contrast this approach with an actively adaptive approach, in which harvest decisions are used in part to produce the learning needed to increase long-term management performance. Our investigation suggests that the passive approach is expected to perform nearly as well as an optimal actively adaptive approach, particularly considering the nature of the model set, management objectives and constraints, and current regulatory alternatives. We offer some comments about the nature of the biological hypotheses being tested and describe some of the inherent limitations on learning in the AHM process

Conditions and Limitations on Learning in the Adaptive Management of Mallard Harvests

In 1995, the United States Fish and Wildlife Service adopted a protocol for the adaptive management of waterfowl hunting regulations (AHM) to help reduce uncertainty about the magnitude of sustainable harvests. To date, the AHM process has focused principally on the midcontinent population of mallards (Anas platyrhynchos), whose dynamics are described by 4 alternative models. Collectively, these models express uncertainty (or disagreement) about whether harvest is an additive or a compensatory form of mortality and whether the reproductive process is weakly or strongly density-dependent. Each model is associated with a probability or weight, which describes its relative ability to predict changes in population size. These Bayesian probabilities are updated annually using a comparison of population size predicted under each model with that observed by a monitoring program. The current AHM process is passively adaptive, in the sense that there is no a priori consideration of how harvest decisions might affect discrimination among models. We contrast this approach with an actively adaptive approach, in which harvest decisions are used in part to produce the learning needed to increase long-term management performance. Our investigation suggests that the passive approach is expected to perform nearly as well as an optimal actively adaptive approach, particularly considering the nature of the model set, management objectives and constraints, and current regulatory alternatives. We offer some comments about the nature of the biological hypotheses being tested and describe some of the inherent limitations on learning in the AHM process