Varieties of Social Explanation


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Consider two ways that the effect E , which is a building burning down, might occur see Figure In one scenario the wiring might short-circuit and overheat, thus causing the wooden framing to burn. In another, a gasoline can might be next to a furnace that ignites and causes the gasoline can to explode. A number of factors here are INUS conditions for the building to burn down. The short circuit C and the wooden framing W together might cause the building to burn down, or the gasoline can G and the furnace F might cause the building to burn down.

Thus, C and W together are exclusively sufficient [S] to burn the building down, and G and F together are exclusively sufficient [S] to burn the building down. Furthermore, the short circuit and wooden framing C and W are unnecessary [U], and the gasoline can and the furnace G and F are unnecessary [U] because the building could have burned down with just one or the other combination of factors.

Finally, C , W , G , or F alone is insufficient [I] to burn the building down even though C is necessary 2138 in conjunction with W or vice versa and G is necessary 2138 in conjunction with F or vice-versa. This formulation allows for the fact that no single cause is sufficient or necessary, but when experts say p. From the perspective of a practicing researcher, three lessons follow from the INUS conditions. First a putative cause such as C might not cause the effect E because G and F might be responsible.

Hence, the burned-down building E will not always result from a short circuit C even though C could cause the building to burn down. Second, interactions among causes may be necessary for any one cause to be sufficient C and W require each other and W and G require each other. In summary, the INUS conditions suggest the multiplicity of causal pathways and causes, the possibility of conjunctural causation Ragin , and the likelihood that social science relationships will appear probabilistic even if they are deterministic.

A specific example might help to make these points clearer.

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Assume that the four INUS factors mentioned above, C , W , G , and F , occur independently of one another and that they are the only factors which cause fires in buildings. Further assume that short circuits C occur 10 percent of the time, wooden W frame buildings 50 percent of the time, furnaces F 90 percent of the time, and gasoline G cans near furnaces 10 percent of the time. Because these events are assumed independent of one another, it is easy to calculate that C and W occur 5 percent of the time and that G and F occur 9 percent of the time.

We simply multiply the probability of the two independent events. All four conditions occur 0. The product of all four percentages.

Thus, fires occur This percentage includes the cases where the fire is the result of C and W 5 percent of the time and where it is the result of G and F 9 percent of the time , and it adjusts downward for double-counting that occurs in the cases where all four INUS conditions occur together 0. Now suppose an experimenter did not know about the role of wooden frame buildings or gasoline cans and furnaces and only looked at the relationship between fires and short circuits.

A cross-tabulation of fires with the short circuit factor would yield Table As assumed above, short circuits occur 10 percent of the time see the third column total at the bottom of the table and as calculated above, fires occur The entries in the interior of the table are calculated in a similar way.

Even though each case occurs because of a deterministic process—either a short circuit and a wooden frame building or a gasoline can and a furnace or both —this cross-tabulation suggests a probabilistic relationship between fires and short p.

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For this table, a standard measure of association, the Pearson correlation, between the effect and the cause is about. If, however, the correct model is considered in which there are the required interaction effects, the relationship will produce a perfect fit. Table Fires by short circuits in hypothetical example total percentages of each event. INUS conditions reveal a lot about the complexities of causality, but as a definition of it, they turn out to be too weak—they do not rule out situations where there are common causes, and they do not exclude accidental regularities.

The problem of common cause arises in a situation where, for example, lightning strikes L the wooden framing W and causes it to burn E while also causing a short in the circuitry C. If lightning always causes a short in the circuitry, but the short never has anything to do with a fire in these situations because the lightning starts the fire directly through its heating of the wood, we will nevertheless always find that C and E are constantly conjoined through the action of the lightning, suggesting that the short circuit caused the fire even though the truth is that lightning is the common cause of both.

But in the situation with the lightning, the fact that short circuits have the capacity to cause fires makes it less likely that we will realize that lightning is the common cause of both the short circuits and the fires. We might be better off in the case where the lightning split some of the wood framing of the house instead of causing a short circuit. In that case, p. For a Humean, the constant conjunction of split wood and fires suggests causation as much as the constant conjunction of short circuits and fires.

Indeed, the constant conjunction of storks and babies would be treated as probative of a causal connection. Since it is not unconditionally true that splitting wood causes fires, the presumption is that some such conditions can be found to rule out this explanation.


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Unfortunately, no set of conditions seem to be successful. Part of the problem is that there are many different types of causal laws and they do not fit any particular patterns. For example, one restriction that has been proposed to ensure lawfulness is that lawlike statements should either not refer to particular situations or they should be derivable from laws that do not refer to particular situations. Furthermore, by this standard, almost all social science and natural science laws e. In short, logical restrictions on the form of laws do not seem sufficient to characterize causality.

The regularity approach also fails because it does not provide an explanation for the asymmetry of causation. The p. When the sun rises, the shadow is long, at midday it is short, and at sunset it is long again. Intuition about causality suggests that the length of the shadow is caused by the height of the flagpole and the elevation of the sun.

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Varieties of Social Explanation: An Introduction to the Philosophy of Social Science

But, using INUS conditions, we can just as well say that the elevation of the sun is caused by the height of the flagpole and the length of the shadow. There is simply nothing in the conditions that precludes this fantastic possibility. The only feature of the Humean approach that provides for asymmetry is temporal precedence.

If changes in the elevation of the sun precede corresponding changes in the length of the shadow, then we can say that the elevation of the sun causes the length of the shadow. And if changes in the height of the flagpole precede corresponding changes in the length of the shadow, we can say that the height of the flagpole causes the length of the shadow. But many philosophers reject making temporal precedence the determinant of causal asymmetry because it precludes the possibility of explaining the direction of time by causal asymmetry and it precludes the possibility of backwards causation.

From a practical perspective, it also requires careful measures of timing that may be difficult in a particular situation. This discussion reveals two basic aspects of the causal relation. One is a symmetrical form of association between cause and effect and the other is an asymmetrical relation in which causes produce effects but not the reverse. The Humean regularity approach, in the form of INUS conditions, provides a necessary condition for the existence of the symmetrical relationship, 24 but it does not rule out situations such as common cause and accidental regularities where there is no causal relationship at all.

A great deal of what passes for causal modeling suffers from these defects Freedman ; ; ; The Humean approach does even less well with the asymmetrical feature of the causal relationship because it provides no way to determine asymmetry except temporal precedence. Yet there are many other aspects of the causal relation that seem more fundamental than temporal precedence. Causes not only typically precede their p. Effects also depend upon causes, but causes do not depend upon effects. Thus, if a cause does not occur, then the effect will not occur because effects depend on their causes.

However, if the effect does not occur, then the cause might still occur because causes can happen without leading to a specific effect if other features of the situation are not propitious for the effect. For example, where a short circuit causes a wooden frame building to burn down, if the short circuit does not occur, then the building will not burn down.

But if the building does not burn down, it is still possible that the short circuit occurred but its capacity for causing fires was neutralized because the building was made of brick.

Casually Explained: Levels of Wealth

This dependence of effects on causes suggests that an alternative definition of causation might be based upon a proper understanding of counterfactuals. The philosopher David Lewis b has proposed the most elaborately worked out theory of how causality is related to counterfactuals.

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It deals directly with singular causal events, and it does not require the examination of a large number of instances of X and Y. The counterfactual approach, however, starts with singular events and proposes that causation can be established without an appeal to a set of similar events and general p.

It only makes sense to evaluate the counterfactual in a world in which the premise is true. Thus, if X is a hammer blow and Y is a glass breaking, then the closest possible world is one in which everything else is the same except that the hammer blow does not occur. If in this world, the glass does not break, then the counterfactual is true, and the hammer blow X causes the glass to break Y.

The obvious problem with this approach is identifying the closest possible world. If X is the assassination of Archduke Ferdinand and Y is the First World War, is it true that the First World War would not have occurred in the closest possible world where the bullet shot by the terrorist Gavrilo Princip did not hit the Archduke?

Or would some other incident have inevitably precipitated the First World War?

Varieties of Social Explanation Varieties of Social Explanation
Varieties of Social Explanation Varieties of Social Explanation
Varieties of Social Explanation Varieties of Social Explanation
Varieties of Social Explanation Varieties of Social Explanation
Varieties of Social Explanation Varieties of Social Explanation
Varieties of Social Explanation Varieties of Social Explanation

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