The asymmetry of causation and backward causation are discussed. The problems are whether asymmetry of causation is objective or subjective, and what backward causation is. First, I survey and criticize three theories about causation: Dowe's fork theory, Menzies and Price's agency theory and Woodward's manipulability theory. Next, I insist that we should distinguish between causal process and causal direction, and that the former objectively exists but the latter does not. Third, I clarify what backward causation is if the causal direction does not objectively exist. I focus on the relative direction of temporal axis in causal process. Forth and finally, I would like to apply my theory to the problem of non-locality in quantum mechanics.

The basic idea of interventionist theories of causation is this: X causes Y iff there is a possible intervention on X for Y, and if the value of X were changed as a result of that intervention, then the value of Y would change. These theories are subdivided into reductive and non-reductive accounts. Reductive accounts, advanced by Menzies and Price (1993), reduce the notion of causation to a non-causal notion of intervention, while according to non-reductive accounts advanced by Woodward (2003), such a reduction is not possible. In the present paper, I investigate causation in algebraic quantum field theory from Woodward's point of view. I define the necessary condition for no causal relationship between the local algebras associated with two spacelike separated region, and show that this condition always holds under the usual axioms of algebraic quantum field theory.

Scientific experiments are often in disputes. Their qualities are challenged. Doubts are casted if their results are proper or fake. Under such polemical circumstances, how did scientists reach agreements on the qualities of experiments and their proper outcomes? By appealing to his idea of ‘experimenters' regress’, Harry Collins rejected an accepted answer to this question, and gave his own. This paper proposes a counterexample to his views that is taken from the ‘measurement networking’ for standard values of fundamental physical constants. Examinations of a sort of meta-analysis; i.e. statistical technique that is conventionally used in the networking, reveal that, in contrast to Collins' answer, the agreements at issues can be attained only in a holistic way and simultaneously within the network.

For the past few decades, the statistical analysis of causation, referred to as causal Bayes-net, has gained wide applicability to many scientific areas including economics, biology, psychology and others. Bayes-nets model the causal relationships with a graph-theoretic structure and evaluates the effect of a causal intervention with the aid of the probabilistic pattern called the Markov Condition. This paper firstly reviews this statistical approach to see how it works in tasks such as the prediction of causal consequence or the evaluation of counterfactual propositions. The success of Bayes-nets in these tasks comes not without philosophical implications. Two related interpretations of causality - the probabilistic reductionism and the interventionist theory - are examined in the second half of the paper. Although both of them suffer from the problem of unfaithfulness, i.e. the probabilistic independence not implied by the Markov Condition, it will be argued that resorting to the underlying mechanism, or the ‘invariance’, helps the interventionists to avoid the problem and to justify some assumptions in the use of Bayes-net.