Every now and then, I come across a link to a paper on academia.edu that looks interesting. I
myself don't have an account on academia.edu, and I don't want
one. This means that in order to look at the paper, I have to go
through the following process.
- I click "Download (pdf)".
- I get confronted with the message: "You must be logged in to
download". I can choose to "connect" with Facebook or Google
or create an account manually.
- I choose the third option, since I don't want academia.edu to
access my Google profile (and I don't have a Facebook account).
- Now I have to fill in a form asking for "First Name", "Last Name",
"Email" and "Password". I enter random expletives in all the fields
because I don't want an academia account, I just want to see the
bloody paper.
- After submitting that form, I get asked whether I have coauthored
a paper in a peer-reviewed journal. I choose "No", fearing that
otherwise I'll have to answer more questions about those papers.
- Next I'm asked to upload my papers. I don't want to upload any
papers, so I click "Skip this step".
- Next I have to fill in my university affiliation: "University",
"URL", "Department", "Position". I enter random expletives.
- Next comes a form where I have to enter my "Research Interests". I
enter some expletives. (Turns out my expletives are a popular research
interest, shared with 32 others.)
- Next I'm told again to "connect" with Facebook, even though I
already chose not to at the start. I click "I don't have a Facebook
account".
- Now, finally, I am presented with a link to the paper I
wanted to have a look at.
As you can imagine, I rarely go through all that hassle. Usually I
look around if I can find the paper somewhere else and give up if I
can't.
Given some evidence E and some proposition P, we can ask to what
extent E supports P, and thus to what extent an agent should believe P
if their only relevant evidence is E. The question may not always have
a precise answer, but there are both intuitive and theoretical reasons
to assume that the question is meaningful – that there is a kind
of (imprecise) "evidential probability" conferred by evidence on
propositions. That's why it makes sense to say, for example, that one
should proportion one's beliefs to one's evidence.
In 2008, I wrote a post on Stalnaker on self-location,
in which I attributed a certain position to Stalnaker and raised some
objections. But the position isn't actually Stalnaker's. (It might be
closer to Chisholm's). So here is another attempt at figuring out
Stalnaker's view. (I'm mostly drawing on chapter 3 of Our Knowledge
of the internal world (2008), chapter 5 of Context (2014),
and a forthcoming paper called "Modeling a perspective on the world"
(2015).)
In "Ramseyan
Humility", Lewis argues for a thesis he calls "Humility". He never
quite says what that thesis is, but its core seems to be the claim
that our evidence can never rule out worlds that differ from actuality
merely by swapping around fundamental properties. Lewis's argument, on
pp.205-207, is perhaps the most puzzling argument he ever gave.
Lewis begins with some terminology.
In The Logic of Decision, Richard Jeffrey pointed out that
the desirability (or "news value") of a proposition can be usefully
understood as a weighted average of the desirability of different ways
in which the proposition can be true, weighted by their respective
probability. That is, if A and B are incompatible propositions,
then
(1) Des(AvB) = Des(A)P(A/AvB) + Des(B)P(B/AvB).
So desirabilities are affected by probabilities. If you prefer A
over B and just found out that conditional on their disjunction, A is
more likely then B, then the desirability of the disjunction goes
up. That seems right.
Superficially, modal auxiliaries such as 'must', 'may', 'might', or
'can' seem to be predicate operators. So it is tempting to interpret
them as functions from properties to properties: just as 'Alice jumps'
attributes to Alice the property of jumping, 'Alice can jump'
attributes to her the property of being able to jump, 'Alice may jump'
attributes the property of being allowed to jump, and so on.
Perhaps the biggest obstacle to this approach comes from quantified
constructions. If 'Alice may jump' attributes to Alice the property of
being allowed to jump, then 'one of us may jump' should say that one
of us has the property of being allowed to jump. But while this is one
possible reading of the sentence, 'one of us may jump' also has a
reading on which it states that it is permissible that one of us
jumps. There is a kind of de re/de dicto ambiguity here, which
suggests that 'may' can not only apply to properties but also to
propositions.
Let's say that an act A is subjectively better than an
alternative B if A is better in light of the agent's information; A is
objectively better if it is better in light of all the
facts. The distinction is easiest to grasp in a consequentialist
setting. Here an act is objectively better if it brings about more
good -- if it saves more lives, for example. A morally conscientious
agent may not know which of her options would bring about more
good. Her subjective ranking of the options might therefore go by the
expectation of the good: by the probability-weighted average of the
good each act might bring about.
"The Philosopher's Index" is a commercial software once widely
used to search for articles in philosophy journals. These days
it is
generally easier and faster to
search on the open internet. (Even the company behind the Philosopher's Index is not quite sure why the Index is still needed.) However, there is one thing the
Index has that can't be found anywhere else: many of its entries
contain abstracts of books and articles, apparently provided by the
authors themselves. These abstracts are often not part of the
published versions, and they can be quite useful to get an
authoritative summary, or to see what the author considered to be the
main point of a paper.
If you spin a wheel of fortune, the outcome -- red or black -- depends
on the speed with which you spin. As you increase the speed,
the outcome quickly cycles through the two possibilities red and
black. As a consequence, any reasonably smooth probability distribution
(or frequency distribution) over initial speed determines an
approximately equal probability (frequency) for red and black. Here is
an example of such a distribution, taken from Strevens.
I've been asked to review Michael Strevens's new book,
Tychomancy. This motivated me to have another look at his
earlier book Bigger than Chaos.
The aim of Bigger than Chaos is to explain how apparently
chaotic interactions in highly complex systems often give rise to
simple large-scale regularities, such as the laws of thermodynamics,
the stability of predator/prey population levels, or the economic
cycle. The basic explanatory strategy, which Strevens calls enion
probability analysis (EPA), consists in aggregating the
probabilistic dynamics for the individual components of a complex
system into a probabilistic dynamics for macro-level features of the
system.