faculty_hiring — Faculty hiring networks (Comp. Sci., Business, History)

Description

Three networks of faculty hiring among PhD-granting departments in the United States (and, for computer science, Canada), in Computer Science (computer_science), Business (business) and History (history). Each node is an institution, and each directed edge $(u, v)$ is a tenure-track or tenured faculty member who received their doctorate at $u$ and was employed as faculty at $v$ at the time of collection, so that multiple edges and self-loops (faculty hired by their own doctoral institution) are present. The data were collected and validated by hand by A. Clauset, S. Arbesman and D. B. Larremore from primary sources (mainly departmental web pages and faculty homepages), covering 205 computer science departments (May 2011 to March 2012), 112 business schools (March to December 2012) and 144 history departments (January to August 2013). Faculty who received their doctorate outside the sampled institutions (mainly from foreign universities) are assigned to an additional source node named "All others".

The networks have the following properties:

(Node) institution: name of the institution.
(Node) pi: the institution's prestige rank, inferred from the hiring network with a minimum violation ranking (lower values mean higher prestige).
(Node) USN2010 (computer science), USN2012 (business), USN2009 (history): the institution's U.S. News & World Report rank closest to the collection period.
(Node) NRC95 (computer science), NRC2010 (history): the institution's National Research Council rank.
(Node) NRC-- (business): empty, since no such rank exists.
(Node) Region: geographic region of the institution: a US Census region (Northeast, Midwest, South, West), Canada, or Earth for the "All others" node.
(Node) Missing values are denoted by a period ".".
(Edge) rank: the faculty member's rank at $v$: assistant (Asst), associate (Assoc) or full (Full) professor.
(Edge) gender: the faculty member's gender, M or F.

Tags

Economic Employment Weighted Metadata

Added

2021-09-02

Citation

A. Clauset, S. Arbesman, and D. B. Larremore, "Systematic inequality and hierarchy in faculty hiring networks." Science Advances 1(1), e1400005 (2015). 10.1126/sciadv.1400005 Sci-Hub

Upstream URL OK

https://aaronclauset.github.io/facultyhiring/

Networks

Tip: click on a column header to sort the list, or hover over it for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
computer_science	206	4,988	24.21	62.95	41.69	2.28	-0.07	0.38	3	1.00	Directed	Unipartite	name pi USN2010 NRC95 Region institution	rank gender	14 KiB	30 KiB	27 KiB	19 KiB
business	113	9,042	80.02	148.21	60.48	1.42	-0.09	0.68	2	1.00	Directed	Unipartite	name pi USN2012 NRC-- Region institution	rank gender	13 KiB	38 KiB	35 KiB	22 KiB
history	145	4,538	31.30	75.92	44.78	1.51	-0.12	0.52	3	1.00	Directed	Unipartite	name pi USN2009 NRC2010 Region institution	rank gender	11 KiB	26 KiB	24 KiB	16 KiB

Ridiculograms^*

computer_science drawing — computer_science

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.