Nice, and the End of Lent Term

Hello everyone!


Last Friday was my last day of class (wow that went really quickly!!).  It feels like it was just a few days ago that I was writing here about the start of Lent Term, and now it’s over.  From here I have until the end of May to study for my exams, which are the first week of June, and the rest of the summer to complete my dissertation, which is due mid-August.  I’m not going to reflect now on everything I’ve learned being at LSE, because that would make me too sad about how my time in London is almost over, so I’ll make a note to be extra reflective this August.  For the time being I’m content to live in the present and to keep building on what I’ve done.



In mid-February, keeping with my New Year’s Resolution to travel more, I visited Nice, on the southern coast of France, and spent a day in Monaco, which is a short bus ride away.  It was wonderful to see the Sea (I was corrected by a local that in Nice, it is the Sea, not the ocean), which was bluer than any water I’ve seen before.  It was a little too cold for me to swim (though some brave locals were in the water), but quite warm enough to walk along the shore and hike to the top of some hills overlooking the water.  I had some delicious cheese, escargot, and rosé, and saw some super big yachts in Monaco.  I had a nice chat with an old philosopher I met on the beach who took me antique shopping and told me that Nice is one of the most relaxing places to live, especially in the off-tourist season when it’s near empty.



Manipulationist Account of Causation

We talked about a few types of causation in my philosophy of science course, and I thought I’d mention here the one I found to be the most convincing: the manipulationist account.  Essentially, X is a cause of Y if intervention on X produces a change in Y, i.e. X must have manipulative control over Y in order for X to be a cause of Y.  An intervention is defined as a change in Y that can occur only as a result of a change in X.  For example, a strong wind can be said to cause me to have dropped my ice cream if changes in the wind’s velocity result in me dropping the ice cream differently or not at all.  Although of course I could not actually change the wind to determine how it affects my ability to hold on to things, I can imagine changes to its speed and direction and the resulting effects.  Stated more simply, X is said to intervene on Y if all of the following are true:

(1) An intervention on X changes the value of Y (but not all changes to X must do so)

(2) All changes in Y must result from the intervention and not another source

(3) The intervention, I, must travel to Y through X and not through another source

(I → X →Y), not (I →Z →Y and I →X) or (I →Y and I →X)

An important part of defining causation is its effect on how we perceive science.  According to the above model (summarized from James Woodward’s manipulationist account), one can differentiate explanatory knowledge from descriptive knowledge (and explanatory sciences from descriptive sciences).  Explanatory knowledge provides control by defining causal relationships, while descriptive knowledge is merely a systematization of observations.  Woodward gives the history of biology as an example.  Biology was a descriptive science until the invention of new instruments and experimental techniques in the early 20th century (such as the microscope) allowed for interventions, and the development of the explanatory field of molecular biology.  I like this account of causation for two reasons that Woodward mentions: (1) it defines causation in a way that applies both to everyday life and to scientific study, and (2) it provides an account of causation that represents the way that scientists themselves think of causality.

A problem for the account is the so called ‘common cause’ dilemma – where one might be fooled into thinking X is a cause of Y because a change in X resulted in a change in Y, when in reality both X and Y are caused by Z.  For example, one could observe that just before thunderstorms appear, barometers show a drop in pressure and all the cows in the field lie down.  The Manipulationist account could lead one to all sorts of strange conclusions, such as ‘when the barometer does not show a drop in pressure, the cows do not lie down; therefore, a low barometer reading causes cows to lie down.’  Likewise, once could conclude ‘because storms only occur after the cows have lied down, cows lying down is a cause of thunderstorms.’

In reality, it is a low pressure system that (1) draws the storm clouds in, (2) results in the barometer showing a drop in pressure, and (3) causes the cows to sense a change in weather is coming and to lie down.  However, all of the above statements of causality are logically sound given the manipulationist account, meaning one must be careful in assigning causal relationships.


As I’m done with classes I’m going to try to see more of the British countryside in the coming weeks (and I hope to study while I’m there), so I’ll try to upload some pictures from those trips as I go.






Woodward, J. (2003) Making Things Happen, Oxford: Oxford University Press, Ch. 1.



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