Missed Article

21 November 2020

I found an article that, had I known of it, I would have noted in my probability paper, A Logic of Comparative Support: Qualitative Conditional Probability Relations Represented by Popper Functions by James Allen Hawthorne
in Oxford Handbook of Probabilities and Philosophy, edited by Alan Hájek and Chris Hitchcock

Professor Hawthorne adopts essentially unchanged most of Koopman's axiomata from The Axioms and Algebra of Intuitive Probability, but sets aside Koopman's axiom of Subdivision, noting that it may not seem as intuitively compelling as the others. In my own paper, I showed that Koopman's axiom of Subdivision was a theorem of a much simpler, more general principle in combination with an axiom that is equivalent to two of the axiomata in Koopman's later revision of his system. (The article containing that revision is not listed in Hawthorne's bibliography.) I provided less radically simpler alternatives to other axiomata, and included axiomata that did not apply to Koopman's purposes in his paper but did to the purposes of a general theory of decision-making.

Final Form

19 November 2020

I wasn't otherwise informed of the change, but when I checked this morning I found that a version of my probability paper had been posted to the First View list (and the listing amongst accepted manuscripts removed). So, except for pagination, the final form has been created. (I hope that the error to which I last directed attention of the productions office was corrected.)

Still in a Bottleneck

9 November 2020

On 3 September, I received a galley proof of my probability paper. Setting aside issues of style,[1] there were various minor problems. Of a bit greater importance was that the paper was reported as received on 20 Februrary 2020, the date that the publisher received it from the editors, which was months after the editors had received it from me. But the most important matter was the replacement in a citation of 1843 with 1943.[2] I responded on the same day, noting most of these issues.[3] On 10 September, I was queried about which version of the MSC I'd used for the code that I'd provided, and as to whether there were truly a space in my surname. Again I responded on the same day.

On 6 October, I received a new galley proof. I found no new problems. All of the minor issues that I'd noted were fixed. However, the paper was still reported as received on 20 Februrary, and the citation still had the wrong year. I decided to ignore the first of these two issues, and simply to note the problem with the citation. Again, I responded on the same day.

I have not since received communication from the production office. My paper remains on the accepted manuscripts list, and has not appeared in the FirstView list.

[1] I think that I just have to accept things such as punctuation being moved within quotation marks even when it's not part of the quotation, spaces being removed from either side of em-dashes, and artefact being respelled artifact, though I use the former for a different notion from the latter.

[2] The first clear frequentist challenge to the classical approach to probability seems to have been made in a paper by Richard Leslie Ellis published in 1843.

[3] One thing that I decided not to note was my discomfort over the space between left-hand quotation marks and quoted formulæ.

Science and the Humanities

7 November 2020

Reading a book first published in 1951, I am reminded that, at one time, the definition of humanities included sciences of human behavior within its scope. Now, one seldom encounters that inclusion in contemporary use, and the Merriam-Webster Dictionary explicitly excludes the study of social relations (though it says nothing explicit about that part of behavior outside of the social).

In the earlier period, there was a question of whether the study of human behavior were fundamentally different from the study of the properties of other things. Those who insisted upon such a difference would speak and write of science and the humanities as if of two separate things.

But the tools by which the physical, biological, and behavioral science were studied were increasingly shared. The physical and biological sciences took-up probability and statistics; the biological sciences have taken-up chemistry, mechanics, and game theory; the behavioral science have taken-up biological explanation and mathematical modelling. All have been affected by the same philosophic theories of method. A dichotomy of science and the humanities cannot prevail so long as the behavioral sciences are included amongst what are called humanities.

Apparently that dichotomy was so dear to some of those who insisted upon it that they attempted its preservation by implicitly changing what they intended with humanities in order to hold fast to it. Of course, the newer definition doesn't maintain the original dichotomy; but replaces it with a new one.

Lack of Infrastructure

26 September 2020
[panel from Kirakira • Sutadī — Zettai Gokaku Sengen by Hanabana Tsubomi in which three students react with dismay at something given to them by a fourth student.  One dismayed student declares 'What is this…?!  This is absolutely filled with symbols I've never seen before…'  Another cries 'I don't even understand what the questions are asking…!!']
(from KiraKira★Study by Hanabana Tsubomi, v 2 ch 18)

My work and the problems that most interest me are difficult to discuss with friends and even with colleagues because so much infrastructure is unfamiliar to them.

Libertine Bayesianism

24 September 2020

As repeatedly noted by me and by many others, there are multiple theories about the fundamental notion of probability, including (though not restricted to) the notion of probabilities as objective, logical relationships amongst propositions and that of probabilities as degrees of belief.

Though those two notions are distinct, subscribers to each typically agree with subscribers to the other upon a great deal of the axiomatic structure of the logic of probability. Further, in practice the main-stream of the first group and that of the second group both arrive at their estimates of measures of probability by adjusting initial values through repeated application, as observations accumulate, of a principle known as Bayes' theorem. Indeed, the main-stream of one group are called objective Bayesian and the mainstream of the other are often called subjective Bayesian.[1] Where the two main-streams differ in practice is in the source of those initial values.

The objective Bayesians believe that, in the absence of information, one begins with what are called non-informative priors. This notion is evolved from the classical idea of a principle of insufficient reason, which said that one should assign equal probabilities to events or to propositions, in the absence of a reason for assigning different probabilities. (For example, begin by assume that a die is fair.) The objective Bayesians attempt to be more shrewd than the classical theorists, but will often admit that in some cases non-informative priors cannot be found because of a lack of understanding of how to divide the possibilities (in some cases because of complexity).

The subjective Bayesians believe that one may use as a prior whatever initial degree of belief one has, measured on an interval from 0 through 1. As measures of probability are taken to be degrees of belief, any application of Bayes' theorem that results in a new value is supposed to result in a new degree of belief.

I want to suggest what I think to be a new school of thought, with a Bayesian sub-school, not-withstanding that I have no intention of joining this school.

If a set of things is completely ranked, it's possible to proxy that ranking with a quantification, such that if one thing has a higher rank than another then it is assigned a greater quantification, and that if two things have the same rank then they are assigned the same quantification. If all that we have is a ranking, with no further stipulations, then there will be infinitely many possible quantifications that will work as proxies. Often, we may want to tighten-up the rules of quantification (for example, by requiring that all quantities be in the interval from 0 through 1), and yet still it may be the case that infinitely many quantifications would work equally well as proxies.

Sets of measures of probability may be considered as proxies for underlying rankings of propositions or of events by probability. The principles to which most theorists agree when they consider probability rankings as such constrain the sets of possible measures, but so long as only a finite set of propositions or of events is under consideration, there are infinitely many sets of measures that will work as proxies.

A subjectivist feels free to use his or her degrees of belief so long as they fit the constraints, even though someone else may have a different set of degrees of belief that also fit the constraints. However, the argument for the admissibility of the subjectivist's own set of degrees of belief is not that it is believed; the argument is that one's own set of degrees of belief fits the constraints. Belief as such is irrelevant. It might be that one's own belief is colored by private information, but then the argument is not that one believes the private information, but that the information as such is relevant (as indeed it might be); and there would always be some other sets of measures that also conformed to the private information.

Perhaps one might as well use one's own set of degrees of belief, but one also might every bit as well use any conforming set of measures.

So what I now suggest is what I call a libertine school, which regards measures of probability as proxies for probability rankings and which accepts any set of measures that conform to what is known of the probability ranking of propositions or of events, regardless of whether these measures are thought to be the degrees of belief of anyone, and without any concern that these should become the degrees of belief of anyone; and in particular I suggest libertine Bayesianism, which accepts the analytic principles common to the objective Bayesians and to the subjective Bayesians, but which will allow any set of priors that conforms to those principles.

[1] So great a share of subjectivists subscribe to a Bayesian principle of updating that often the subjective Bayesians are simply called subjectivists as if there were no need to distinguish amongst subjectivists. And, until relatively recently, so little recognition was given to the objective Bayesians that Bayesian was often taken as synonymous with subjectivist.

An Exercise in Economic Thinking

13 July 2020

Yester-day, I posted a problem to Facebook:

Assume that the market for CEOs of large corporations is very tight, with directors competing ferociously for candidates. How will the burden of a tax on compensation to CEOs be distributed between the CEOs and the stockholders? If a heavily progressive tax is placed on the incomes of CEOs, what will happen to the pre-tax income levels of these CEOs?

So far, for whatever reasons, no one has offered answers, though the answers should be obvious. What makes the exercise interesting is the inversion of the answer to the second question. A great many people who could correctly and quickly answer the question itself it would almost surely miss the inversion if not asked the question.

Writing Efforts

5 July 2020

For several months, just two manuscripts were in the listing of manuscripts accepted by The Review of Symbolic Logic, one on an application of modal logic to set theory which article had been listed on 4 October and mine on probability which had been listed on 20 February. On 25 June, another was added, followed by nine more on 29 June; on 2 July, four more.

I don't know why the oldest two on the list have still not been typeset and moved to the FirstView list. And I don't think that my article will find many readers before it has, further, been assigned to a specific issue. It seems unlikely that the last will happen before 2021.

I have been working on a paper concerned with De Morgan's contribution to an area of probability theory. I had wanted to mention that contribution in the introduction to my probability paper, but saw no way of doing it that would be succinct without seeming occult. I began the new paper thinking that I would finish it in a very few days, but as I engaged in some of the requisite research I found that the task of properly explaining things was going to be still more challenging than I had anticipated.

In the end, the paper on De Morgan will be seen as a minor contribution to the history of thought. Had I known at the beginning how troublesome would be the task of writing it, I would have postponed the undertaking.

Making Your Vote (or Non-Vote) Count

14 June 2020

In nearly every election of a state official, even those in which only a few hundred voters participate, the margin of victory is more than one vote. What that means is that, if any one voter had refrained from voting, or if any one abstaining voter had not abstained, the candidate who won would still have won. Some people — even some very intelligent people — conclude that the vote of an individual has no efficacy beyond that of other acts of expression. Those people are missing something.

Indeed, one's vote or refusal to vote has absolutely no effect on the election at hand. There are various things that one can do prior to the election which may help one candidate to achieve a margin of victory, or prevent another from achieving such a margin. But one's own vote isn't going to make any difference in that election.

However, as potential candidates and parties decide what to do with future elections in mind, they look at margins of victory in past elections. Potential candidates decide whether to run and, if they choose to run, how to position themselves, informed by those margins. Parties decide their platforms and whom to nominate, informed by those margins. With large margins in their favor, they feel free to alienate a greater number of potential voters; with small margins or losing margins, they consider what to do differently in order to pull voters who previously voted for another, or who didn't vote at all.

Thus, an individual vote or the decision not to vote has a small effect — but its only effect — on later elections and on behavior of those who are acting with concern for later election.

The least effective thing that a potential voter can do is to vote for a candidate whom he or she dislikes. People in America who have held their noses to vote for the Democratic or Republican nominee in order to stop the nominee of the other party did worse than to throw-away their votes; they have helped to ensure that the next pair of choices would likewise be disagreeable, and that the behavior of officials in the mean time would likewise be disagreeable. It is only if one genuinely thought that one of these candidates were worthwhile that one should have voted for him or for her, and then still only to affect the next election and interim behavior of officials.

The most effective thing that a potential voter as such can do is to vote for a candidate of whom that voter approves, even if that candidate has no chance of winning, or to submit a ballot from which no candidate receives a vote. An increasing number of people are doing the latter, either in expression that no candidate is worthy, or to challenge the legitimacy of the process in a way that makes it difficult for these people to be dismissed as apathetic by apologists for the process.

Stick That in Your Lexicon!

23 May 2020
bru·to·ri·al /bruːˈtɔːriəl/ adjective & noun
A. noun. An otherwise useless tutorial that one is not permitted to forgo.
B. adjective. Of or pertaining to a brutorial.