how many people applied for jobs in Fall 2024?

Hello! In Fall 2024, I sent out surveys to search committee chairs to get a sense of how many people are on the job market. Thank you to everyone who completed the survey. And a very special thanks to Kate Ferrell for her help in compiling names and emails.

I sent out 229 surveys for jobs advertised between October 1, 2024 and January 10, 2025. I received 72 responses, which gives a margin of error around +/-9%.

The average number of applicants from the responses I received is 137.5. So the average number of people applying for a job is, given some big assumptions, in the ballpark of 125 to 150. The really big assumption is that my sample is representative of all jobs. There are two reasons to think the sample isn't representative. First, completion is voluntary, so there's that bias. Second, among replies, jobs at universities with PhD programs are over-represented in the sample. Roughly 1/3 of the jobs advertised in my dataset were at PhD-granting institutions but around 1/2 of the replies I received were from PhD-granting institutions. So I think the 125-150 range is roughly right, but there's a lot of wiggle room.

First up, the distribution of applicants by program:

Medians were used instead of means because, for both BA and PhD programs, higher values were inflating the averages.

The largest values in the Doctorate facet are 628 and 638 applicants. These were a postdoc and TT positions at R1's. I can appreciate people wanting to shoot their shot. The smallest value for Doctorate programs is seven. Seven! The job is a one-year sabbatical replacement at an R1.

The maximum for BA programs is 330 for a Metaphysics and Epistemology TT position with a 3/2 load. The minimum? 41 for an open rank, open AOS. Teaching load wasn't indicated but the respondent reported that the person hired would spend about the same amount of time teaching and researching.

For MA programs, the max is 207 for a TT position in value theory; the min is 34 for an open AOS, open rank hire.

Clearly, the number of people applying to any given job can vary pretty wildly. Let's first see if the character of the position is relevant (i.e. fixed-term, TT, etc.)

That did not help, but there are a few interesting things to notice. First, for TT positions at PhD programs, there's no obvious correlation between program status and number of applications. The fact that there are so many "Doctorate" values next to each other reflects the relative higher volume of responses from PhD programs.  Next, fewer people are applying to fixed-term positions compared to TT. The ceiling on applications to fixed-term positions is roughly equivalent to the 80th percentile of volume of applications for TT positions. (The same is true for fixed-term positions and Postdoc positions.) This seems intuitive in a sense: of course people are going to prefer long-term stability. But also: some job is typically better than no job; the rent won't pay itself.

Let's look at some of the characteristics of the top and bottom quartile for applicant volume:

"End" says whether that row came from the top quartile (i.e. top 25%) or bottom quartile (i.e. bottom 25%). "Frequency" is how often the AOS/degree-type pairing showed up in each quartile. "Overall frequency" is how many times that pairing showed up in the data set. "Ratio" is the ratio of frequency to overall frequency. A ratio of 1 indicates that that pairing was every instance of that pairing in the dataset. I don't think those entries tell us much given their low initial frequencies in the data.

All five AOS's show up in the top and bottom quartiles, same with the kind of degrees conferred, but there might be a weak interaction effect between AOS and degree-type.  Science, logic, and math for PhD-granting institutions show up more often in the top quartile (three times) compared to the bottom (one time). The same goes for for open and PhD-granting institutions: seven times in the top quartile and twice in the bottom. Finally, an AOS of value theory for PhD-granting programs showed up more often in the bottom quartile (four times) compared to the top quartile (once).

Converting the co-occurrences to dummy variables and checking for correlation coefficients, there are a few cases to note. Among the bottom quartile we find:

1. PhD and history/traditions ( .24)
2. PhD and metaphysics & epistemology (.24)
3. MA and value theory (-.32).

Among the top quartile, we find:

1. PhD and science, logic, and math (.24)
2. BA and history/traditions (.29)
3. BA and open (-.2)

Unfortunately, none of these correlations are significant at p < .05. Or p < .10. Or p <.30. Let's just say that the p-values were all really high.  *cue sad trumpets*

Now let's look at the range of application-volume by AOS and program status, and then volume by AOS and contract type:

For every facet: the vertical grey line is the median for that facet; the points on the horizontal lines are the median for the facet and y-axis categories; and the error bars are the maximum and minimum values for the facet and y-axis categories. Some of the takeaways include:

1. you'll have less competition applying for fixed-term positions
2. you'll typically have less competition applying for positions at BA-granting institutes (except for M&E positions, but that might be an outlier for this year)
3. open AOS invites everyone and their grandmothers to apply, especially if it's a TT or postdoc at an R1.

The only one of these that's surprising, to me at least, is (2). But the data behind (3) can invite some strategic applying. A committee sifting through 600 applications is going to need some fast-and-ready heuristic. I remember at one APA session a dozen years ago, one well-known philosopher at an R1 said they used PhD pedigree as the initial screening: Phil Gourmet top-10 to the right, everyone else to the left.

As I'm planning for next year's survey, I'm going to add questions about whether the job is exclusively for philosophers, is in industry, and some more about the character of the university (e.g. private or public?) If you have any thoughts on questions you'd like to see on the survey, please drop me a line!

That's all for now. Thanks for reading. The dataset and R script are available under "Blog Data"