Gender Inequalities in Archaeology plays out in NSF funding

Posted on March 11, 2014

I had no plans to write this post. That is because when I got the National Science Foundation data on archaeology grants it did not come with gender or sex of PIs. However, yesterday when I was looking at the top PIs, in terms of number of grants and amounts, for NSF grants to archaeology projects I noticed a significant disparity in the number of men and women receiving grants. Women barely appear in the top grant receivers.

So last night, I took a sample of years and looked at the number of male and female PIs receiving NSF grants for archaeology projects. I looked at the years 1985, 1990, 1995, 2000, 2005, 2010, and 2013. The results were:

	Count Men	Count Women	Men Total Amount	Women Total Amount
1985	24	4	$6,197,712.73	$1,178,342.40
1990	52	15	$5,265,291.62	$1,749,581.93
1995	76	23	$6,954,844.11	$5,121,814.92
2000	77	27	$9,850,983.12	$3,302,724.19
2005	80	44	$16,338,412.36	$4,303,664.08
2010	112	47	$18,067,522.76	$5,267,721.68
2013	80	45	$10,862,518.00	$5,643,121.00

The numbers are adjusted for inflation to 2013 dollars. The numbers are slightly misleading because PIs can also be the faculty advisers for PhD dissertation grants. These grants are put in by students and so it should be their genders/sexes we look at. Here are the number of those grants that are from students, again amount adjusted for inflation:

	Count Student Men	Count Student Women	Men Student Amount	Women Student Amount
1985	0	0	$-00	$-00
1990	7	7	$99,173.38	$137,517.71
1995	18	8	$301,194.75	$126,946.28
2000	17	15	$263,474.10	$232,652.61
2005	23	15	$320,736.34	$188,684.43
2010	16	25	$300,966.18	$416,816.50
2013	15	14	$357,914.00	$314,063.00

This brings the PI, non-dissertation grants to the following numbers:

	Count Men	Count Women	Men Amount	Women Amount
1985	24	4	$6,197,712.73	$1,178,342.40
1990	43	10	$5,118,696.25	$1,659,486.21
1995	51	22	$6,539,454.57	$5,109,063.43
2000	54	18	$9,493,289.96	$3,164,290.65
2005	57	29	$16,020,449.31	$4,112,206.35
2010	87	31	$17,606,617.12	$5,010,844.64
2013	63	33	$10,457,200.00	$5,376,462.00

Removing PhD students only slight changes the numbers. What the data shows is that there are significantly fewer women leading archaeology projects than there are men. This does not mean that the NSF is discriminating against women. In fact, women have roughly the same percentage of accepted grants as men. The problem is that fewer women apply for NSF grants. Here is the breakdown for all NSF grant applications for the last few years:

	2005	2006	2007	2008	2009	2010	2011	2012
Female Applications	8,266	8,510	9,197	9,431	9,727	11,903	11,488	10,795
Male Applications	31,456	31,482	32,650	32,074	32,091	38,695	35,211	32,932
Total	39,722	39,992	41,847	41,505	41,818	50,598	46,699	43,727
Female Applications	21%	21%	22%	23%	23%	24%	25%	25%
Male Applications	79%	79%	78%	77%	77%	76%	75%	75%

75% of the applications put into the NSF are from men. The reason women are not getting as many NSF grants as men in archaeology is because fewer women are applying. Fewer women are applying because well there are fewer women in tenure track positions at universities, the main recipients of NSF grants. Until archaeology fixes its gender problems we are going to see this sort of distribution over and over again.

My slightly insensitive methods

Because the data I had did not come with the sex or gender information I had to base my assumptions on names. Of course I went beyond placing people by the name of John in the male category. I went and looked up their profiles online or their digital trails. I then used descriptions of them e.g. ‘he did this dig’, ‘she excavated this’, etc. To assign sex to the PIs. However, this is me assigning them sexes and genders and not them self identifying. This meant I have overlooked transgender and transsexual or any of the categorizes of third genders. So I humbly apologize if I have miss characterized anyone.

Surprisingly there was only one or two people I could not find an online profile for. So I am very confident that this data is accurate in terms of finding the right people and characterizing them into at least one of two categories.

There were 706 grants for the years in question