LeWitt (1968) x Conway (1970) 
Divide a wall into a square grid. Mark arbitrary grid elements with a horizontal line about one-fifth of the way down in the square.

For every cell that was marked to begin with, if it is adjacent to two or three marked squares, mark it with another horizontal line about two-fifths of the way down in the square.
For every unmarked cell, mark it with a line if exactly three of the adjacent grid elements are marked.

Repeat with lines horizontal lines three-fifths of the way down, based on the previous lines.

Continue for a total of twenty sets of lines: The fifth set of lines will be at the bottom of the squares. For the sixth set of lines, mark vertical lines one-fifth of the way across the square... and so on. For the eleventh set of lines, mark diagonal lines one-fifth of the way across. For the sixteenth set, mark diagonal lines which slope in the other direction.

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Cited more often than the norm 
Justin at Daily Nous quotes the statistic that "82 per cent of articles published in humanities are not even cited once." Turning this around, only 18% are cited.

I was curious about how my own papers fared in this regard. Starting with data from Google Scholar and correcting some, 68% of my publications have been cited. One of the corrections was to dismiss articles which were only cited by me in another article. Counting self-citations, the rate jumps to 78%.

In a more self-serving mood, but the quality of my work is only one factor here.

Another factor is that all of my papers are readily available on-line. Once there's a draft worth sharing, I post it to my website. I update it with my final draft once it's accepted for publication, and I continue to make it available. The result is that people who are puttering around on a topic are likely to come across my work, and then they can cite me. This is certainly how forall x, my open-access logic textbook, has come to be cited 11 times. And I have some conference papers and working drafts which have been cited even though they've never been available anywhere but on my website.

In discussions of whether to post papers on-line or not, people underrate the advantages. People who notice my work because it's on-line almost never tell me about, but sometimes they do cite me.

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Counting journals that count 
There is administrative pressure, for purposes of tenure and promotion, to list the top philosophy journals. Some disciplines have lists which are approved by their professional organizations. So people from outside the department are sometimes incredulous that philosophy doesn't.

But we don't. Letter writers for T&P cases tend to say this but then waive their hands at the relative status of various journals, possibly linking to a blog post or something.

I have recently thought that it would be good to have a general statement about this for administrative purposes, rather than putting something together on an ad hoc basis for every case. Below the fold is a draft of what a general statement might look like. It's an alpha version, and I am not confidently committed to other the contents or the form of presentation. So quoting it without that proviso is likely to earn my wrath. Talking about it as a possibly half-baked blog post is fine, though, and I'd appreciate feedback.
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Cleaning Chekhov's Gun 
I wrote most of this years ago, and I stumbled across the file recently while working on something else. I'm sticking it here, like you do.
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Struck by a semirealism 
In a number of recent articles, Bence Nanay has argued for singularist semirealism. It's an anti-realist view about natural kinds which holds that particular tokens of properties exist with various degrees of similarity and dissimilarity among them, but that there are not any natural property types. The view is similar to Anjan Chakravartty's semirealism, which holds similarly that the world consists of property instances more or less sociable with one another, and that the clusters of sociability which science picks out are not somehow special in nature.

Nanay writes:
Some pairs of property-tokens are closer together in the property-space; they resemble each other more than others. But property-types are our arbitrary ways of delineating regions of this property-space. The property-space does not have joints: it consists of lots of property-tokens, some close together, some further away from each other. (2013, p. 377)

His approach seems to be more deeply metaphysical than mine. Nanay is most centrally concerned with whether a natural kind is a thing in the world that exists. I am concerned centrally with the extent to which the world constrains scientific categorization. I am happy to say that categories which uniquely allow successful science would be natural kinds regardless of whether there is an entity the deep ontology of the world which corresponds to that category. I am also willing to allow that kinds can be more or less natural, to the degree that the world condemns alternative taxonomies to failure.

Nevertheless, Nanay argues that singularist semirealism coheres with scientific practice. The reason is "that the two main tools of actual scientific practice, experimentation and measurement, are practices involving property-tokens and not property-types" (2011, p. 189; 2013, p. 383). This seems wrong to me for at least two reasons.

First: If a scientist were given a table of data which was just numbers or magnitudes, she'd have no use for it. Measurements necessarily have units. So measuring the masses and lengths of 10 samples necessarily requires measuring the masses as masses and the lengths as distances. Each singular property property must fit into a category scheme, and so measurement is impossible without kinds.

Second: It ignores the distinction between what Bogen and Woodward call data and phenomena. Singular measurements are data which are always subject to error and variation. Although data play an important evidential role, scientists don't primarily care about data. They care about phenomena which data instantiate. The phenomena are the curves or patterns which we think the data would trace out if it weren't for noise and error. When scientists repeat an experiment, they do not expect to produce precisely the same data as earlier experiments. Rather, they expect to get data which (once reduced by standard formal methods) will yield the same phenomena. So measurement and experiment are about general phenomena-types rather than singular data-tokens.

References

Bogen and Woodward 1988. Saving the Phenomena. PhilRev, 97(3): 303-352.

Chakravartty 2007. A Metaphysics for Scientific Realism, Cambridge University Press.

Nanay 2011. What If Reality Has No Architecture? The Monist, 94(2): 181-197.

Nanay 2013. Singularist Semirealism. BritJPhilSci. 64: 371-394.

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