Causation as production

My diagnosis of why Kim thinks that Exclusion is virtually analytic is that he is thinking of causation as production. If one thinks about causation in this way, then it is quite natural to see Exclusion as virtually analytic. If P x, t) literally produces Q(z, t ), then it does appear that there is no work left for any other event F x, t) to do as far as producing Q(z, t ). Kim also seems to think of causal relation as involving the transfer of some quantity, causal oomph, from the cause that brings the effect into existence. It is not surprising, then, that he would think not only that a second dose of oomph from F(x, t) is not needed to produce Q(z, E) but also that there isn t even any place for it. 

Kim (2007) suggests that the truth makers of counterfactuals or the counterfactuals that go along with mental causation involve causation as production. This is correct if one has in mind the fundamental physical laws evolving fundamental physical states. But Kim is more likely thinking of what 1 called local production. Relations of local production are not the truth makers of counterfactuals on Lewis s account. The fundamental laws and fundamental physical state are the ultimate truth makers of both kinds of causal relations. 

Causation as production fits ill with contemporary physics. Russell (1913) famously said that causation so understood is a relic of a bygone age, surviving, like the monarchy, only because it is erroneously supposed to do no harm. (p. 661)... 

What Russell has in mind is that the fundamental laws and facts of physics do not mention causality. Further, those laws relate the totality of the physical state at one instance to the totality at later instances. [Foomote Or a little more correctly a region of the state at time t is related by law to the states in its backward light cone. This point which is often neglected by philosophers is forcefully made in Latham (1987) and Field (ms.). (661)]. They do not single out parts of states at different times as being causally related. If one wants to think of causation as production then one has to say that the entire micro physical state at t produces the state at t. (p. 661)... 

England that the Committee on Safety of Medicines had written to prescribers in 1995 stating that three unpublished studies on the safety of combined oral contraceptives in relation to venous thromboembolism had indicated about a two-fold increase in the risk of such conditions compared with the preceding generation of products. This issue of a two-fold increase became crucial to the case. For reasons of causation, as the Judge put it, the claimants had accepted the burden of proving that the increase in risk was not less than two-fold. 

Examination of product control charts is most useful in trying to distinguish between process-related or non-process-related causes.Trend analysis of key production parameters and attributes could assist in localizing a possible cause of the OOS. For example, if the potency of the product has been trending higher than usual for the last few batches produced (and the OOS resulted from an upper limit failure), this could be indicative of such causations as inaccurate moisture analysis or operator compensation error, error in the batch record, weighing error due to balance or scale bias, change in excipient purity which could impact functional characteristics or failure to maintain and/or calibrate apiece of equipment. 

The real tragedy is our immutable belief in nonsense causation factors, such as lack of common sense and carelessness. In every failed woik system, the individual makes up onfy one component of the reason for failure. A more constructive mindset could be to always view causation as failure in a system. And a system failure will alw s result through human error in combination with other factors, never through the lone fault of the individual. Consequently, all accident investigation results must identify the role of the environment, the machinery, the materials and the procedures as other causation factors when, and if, human error is identified as a reason for the failure. This approach would largely ignore the adversarial ramifications of accident reporting in favour of a more productive outcome focused solefy on prevention of system failure in the future. 

In the debate about the toxic effects of dyes and chemicals, there is no doubt that carcinogenic effects are perceived by the general public as the most threatening. Chemicals remain a focus for this concern in spite of the weight of evidence that they make only a minor contribution to the incidence of cancer [60,67,83]. The generally accepted estimate of cancer causation, based on mortality statistics, indicates that only 4% of all cancer deaths are attributable to occupational exposure. Another 2% are considered to arise from environmental causes and 1% from other forms of exposure to industrial products. 

The Doll-Peto estimates, and others as well, nevertheless suggest a primary role for lifestyle factors, not chemical pollution and industrial products, in cancer causation. 

As discussed earlier, forensic pharmacology and toxicology are not limited to the study of drugs of abuse or poisons. These fields of science also have a growing role in the legal system to help resolve civil issues related to chemical exposure and cancer causation, medical malpractice as a result of drug interactions, and product liability issues. 

When the effect of exposure to a chemical is the production of a cancer, it is sometimes assumed, for instance, by regulatory agencies such as the U.S. Environmental Protection Agency (EPA) that the dose-response curve passes through zero. Thus, it is not like the dose-response curve we have been discussing above where there is a threshold. The zero threshold dose response is predicated on the belief that the causation of cancer by a genotoxic mechanism is a stochastic (chance) event, in which a reactive chemical binds to and damages or alters DNA (see chap. 6). 

The propriety of this kind of mental leaping is one of the most controversial aspects of toxic tort and occupational disease cases, where causation often cannot be properly formulated as a yes-or-no fact. Instead, parties rely on evidence of increased risk or enhanced probability of disease which may or may not be attributable to defendant s conduct. The inquiry becomes one of the existence and magnitude of a fact probability. Therefore, understanding the dual nature of probability, as both a factual statistical quantity (fact probability) and a measure of strength of belief (belief probability), becomes important. Unfortunately, fact probability and belief probability have not been kept analytically distinct. Courts have collapsed the requirements for burden of production and burden of persuasion into one test that blurs plaintiff s twofold task of defining not only the facts or elements to be proved but also the amount of credence to be accorded a fact in support of a finding. When a judge tells a jury that plaintiff must show that causation is more likely than not, she/he risks confusion. Does she/he mean that the fact of causation which plaintiff must prove (burden of production) is not traditional true-or-false (100% vs. 0%)... 

Concern over haphazard and unrecognized transfer of preponderance of evidence or more likely than not standards from the burden of persuasion to the burden of factual proof (burden of production) involves more than idle semantics. The adverse effects of failure to undertake a deliberate, two-step probabilistic analysis include (a) undue preference for particular probabilities of causation found in one epidemiologic study, especially when meta-analysis of multiple studies is not possible or available (b) unrecognized lowering of the burden of production with concomitant stiffening of the burden (standard) of persuasion (c) inappropriate fixation on simplistic quantitative rules such as the >50% likelihood rule and (d) poorly reasoned opinions because courts fail to explain exactly how they apply the >50%, more-likely than-not rule. 

Judicial decisions in nonregulatory contexts such as toxic tort and product liability suits are likewise inconsistent in their consideration of the linear, no threshold model. As in the regulatory context, most cases find no problem with an expert s reliance on a risk assessment using the linear model. In a handful of cases, however, the court rejects reliance on a linear dose-response assumption. Eor example, one court in addressing the cancer risks from a low concentration of benzene in Perrier held that there is no scientific evidence that the linear no-safe threshold analysis is an acceptable scientific technique used by experts in determining causation in an individual instance (Sutera 1997). Another court decision concluded that [t]he linear non-threshold model cannot be falsified, nor can it be validated. To the extent that it has been subjected to peer review and publication, it has been rejected by the overwhelming majority of the scientific community. It has no known or potential rate of error. It is merely an hypothesis (Whiting 1995). The inconsistency and unpredictability of judicial review of risk assessments adds an additional element of uncertainty into the risk assessment process. 

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