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Acceptability
Acceptability is the characteristic of a thing being subject to acceptance for some purpose. A thing is acceptable if it is sufficient to serve the purpose for which it is provided, even if it is far less usable for this purpose than the ideal example. A thing is unacceptable (or has the characteristic of unacceptability) if it deviates so far from the ideal that it is no longer sufficient to serve the desired purpose, or if it goes against that purpose.
Acceptability is an amorphous concept, being both highly subjective and circumstantial; a thing may be acceptable to one evaluator and unacceptable to another, or unacceptable for one purpose but acceptable for another. Furthermore, acceptability is not necessarily a logical or consistent exercise. A thing may be sufficient to serve a particular purpose but in the subjective view of the decision maker be unacceptable for that purpose. Philosopher Alex Michalos writes that "[t]he concept of acceptability is as ambiguous and troublesome as probability, confirmation, belief, justice, etc.", and assigns two potential meanings to the term with respect to the possible acceptability of hypotheses. Acceptability is a fundamental concept in numerous fields, including economics, medicine, linguistics, and biometrics.
Concepts of acceptability that have been widely studied include acceptable risk in situations affecting human health, and acceptable loss in particularly dire situations. The idea of not increasing lifetime risk by more than one in a million has become commonplace in public health discourse and policy. It is a heuristic measure. It provides a numerical basis for establishing a negligible increase in risk. Comparable concepts include an acceptable level of violence, or an acceptable daily intake of hazardous substances.
Environmental decision making allows some discretion for deeming individual risks potentially "acceptable" if there is a less than one in ten thousand chance of increased lifetime risk. Low risk criteria such as these provide some protection for a case where individuals may be exposed to multiple chemicals e.g. pollutants, food additives or other chemicals. In practice, a true zero-risk is possible only with the suppression of the risk-causing activity.
Stringent requirements of 1 in a million may not be technologically feasible or may be so prohibitively expensive as to render the risk-causing activity unsustainable, resulting in the optimal degree of intervention being a balance between risks vs. benefit. For example, emissions from hospital incinerators result in a certain number of deaths per year. However, this risk must be balanced against the alternatives. There are public health risks, as well as economic costs, associated with all options. The risk associated with no incineration is potential spread of infectious diseases, or even no hospitals. Further investigation identifies options such as separating noninfectious from infectious wastes, or air pollution controls on a medical incinerator.
Acceptable variance is the range of variance in any direction from the ideal value that remains acceptable. In project management, variance can be defined as "the difference between what is planned and what is actually achieved". Degrees of variance "can be classified into negative variance, zero variance, acceptable variance, and unacceptable variance". In software testing, for example, "[g]enerally 0-5% is considered as acceptable variance" from an ideal value.
Acceptance testing is a practice used in chemical and engineering fields, intended to check ahead of time whether or not a thing will be acceptable.
From a logical perspective, a thing can be said to be acceptable if it has no characteristics that make it unacceptable. Various logic formulations of this principle have been developed, for example, that "a theory Δ is acceptable if for any wff α, Δ does not prove both α and ¬α", and that "the acceptability of a proposition P in a system S depends on its coherence with the propositions in S". Notably, Dov Gabbay, et al., have observed that something that is logically acceptable may not be subjectively acceptable to a given individual, and vice versa:
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Acceptability
Acceptability is the characteristic of a thing being subject to acceptance for some purpose. A thing is acceptable if it is sufficient to serve the purpose for which it is provided, even if it is far less usable for this purpose than the ideal example. A thing is unacceptable (or has the characteristic of unacceptability) if it deviates so far from the ideal that it is no longer sufficient to serve the desired purpose, or if it goes against that purpose.
Acceptability is an amorphous concept, being both highly subjective and circumstantial; a thing may be acceptable to one evaluator and unacceptable to another, or unacceptable for one purpose but acceptable for another. Furthermore, acceptability is not necessarily a logical or consistent exercise. A thing may be sufficient to serve a particular purpose but in the subjective view of the decision maker be unacceptable for that purpose. Philosopher Alex Michalos writes that "[t]he concept of acceptability is as ambiguous and troublesome as probability, confirmation, belief, justice, etc.", and assigns two potential meanings to the term with respect to the possible acceptability of hypotheses. Acceptability is a fundamental concept in numerous fields, including economics, medicine, linguistics, and biometrics.
Concepts of acceptability that have been widely studied include acceptable risk in situations affecting human health, and acceptable loss in particularly dire situations. The idea of not increasing lifetime risk by more than one in a million has become commonplace in public health discourse and policy. It is a heuristic measure. It provides a numerical basis for establishing a negligible increase in risk. Comparable concepts include an acceptable level of violence, or an acceptable daily intake of hazardous substances.
Environmental decision making allows some discretion for deeming individual risks potentially "acceptable" if there is a less than one in ten thousand chance of increased lifetime risk. Low risk criteria such as these provide some protection for a case where individuals may be exposed to multiple chemicals e.g. pollutants, food additives or other chemicals. In practice, a true zero-risk is possible only with the suppression of the risk-causing activity.
Stringent requirements of 1 in a million may not be technologically feasible or may be so prohibitively expensive as to render the risk-causing activity unsustainable, resulting in the optimal degree of intervention being a balance between risks vs. benefit. For example, emissions from hospital incinerators result in a certain number of deaths per year. However, this risk must be balanced against the alternatives. There are public health risks, as well as economic costs, associated with all options. The risk associated with no incineration is potential spread of infectious diseases, or even no hospitals. Further investigation identifies options such as separating noninfectious from infectious wastes, or air pollution controls on a medical incinerator.
Acceptable variance is the range of variance in any direction from the ideal value that remains acceptable. In project management, variance can be defined as "the difference between what is planned and what is actually achieved". Degrees of variance "can be classified into negative variance, zero variance, acceptable variance, and unacceptable variance". In software testing, for example, "[g]enerally 0-5% is considered as acceptable variance" from an ideal value.
Acceptance testing is a practice used in chemical and engineering fields, intended to check ahead of time whether or not a thing will be acceptable.
From a logical perspective, a thing can be said to be acceptable if it has no characteristics that make it unacceptable. Various logic formulations of this principle have been developed, for example, that "a theory Δ is acceptable if for any wff α, Δ does not prove both α and ¬α", and that "the acceptability of a proposition P in a system S depends on its coherence with the propositions in S". Notably, Dov Gabbay, et al., have observed that something that is logically acceptable may not be subjectively acceptable to a given individual, and vice versa: