The Effects of Co-Supervision and Lab Placement on Social Networks in a Graduate Biology Program

C. Owen Lo Ph.D. Candidate University of British Columbia, Canada

Presenter

Presentation Outline

Introduction General Social Network Consulting Social Networks Comments & Feedback

Working on Walls (WOW) Project

• Part of an NSERC-CREATE endeavor ▫ Canadian governmental funding ▫ 6-year project

• Focuses on plant cell wall studies ▫ Interdisciplinary ▫ 8 faculty members, 3 post-doc fellows, 8 trainees

Data collection & Analysis

• Data collection ▫ Electronic Questionnaire: LimeSurvey ▫ April 11 to May 11, 2011 ▫ 19 surveys were collected

• Data analysis ▫ UCINET 6 (maps and statistics) ▫ SPSS (statistics)

General Questions

• What is the pattern of the 1) general social network, and 2) consulting networks?

• Have co-supervision and lab-placement increased the network interaction? and have the professional-development activities increased the network interaction?

• What are other factors that might have influenced the network interaction?

Pattern examination of the WOW social interaction

• Cut-point: zero • 2-step: all nodes • Core-peripheral index: 0.48

Density matrix- WoW network

Core Peri.

Core .87 .41

Peri. .41 .20

General traits of the WOW social interaction

• Overall density: 0.65 • Reciprocity: 65 % • Average ties: 12.5

• Incoming: 11.1 • Outgoing: 10.1

• EI indexes: • 0.23 (rank) • 0.73 (primary lab)

* Colors denote rank titles

Co-supervision, lab-placement & the general interaction

Correlations: • with supervision matrix r = .26 (p < .001)

• with lab-placement/co-supervision matrix

r = .45 ( p < .001)

t-test: Z= 1.94 ( p< .05, one tailed)

* Colors denote various laboratories

Professional development & the general networking

Density PIs PDFs Trs.

PIs .75

PDFs .37 1.0

Trs. .53 .83 .93

* Color denotes rank

A logistic regression model IV B Std.

Err. df Sig.

Power distance -.158 -275 1 <.001

Any lab-association .207 .221 1 <.001

Aggregated sociability 2.760 .509 1 <.001

Cox & Snell R² = .476, correct prediction rate: 89%

• Independent variable: power distance lab-association aggregated sociability gender difference linguistic closeness

• Dependent variable: 171 possible ties among 19 nodes (dichotomous)

General traits of the problem-solving consulting network ?

• Density: 0.18 ▫ incoming ties: 3.3 ▫ outgoing ties: 3.8

• Reciprocity: 17% • E-I index: 0.44 ▫ internal ties: 30 ▫ external ties: 78

PIs PDFs Tr.

PIs 0.30 0.13 0.05

PDFs 0.21 0.50 0.00

Tr. 0.23 0.38 0.14

* Colors denote various laboratories

General traits of the new idea consulting network ?

• Density: 0.14 ▫ incoming ties: 2.5 ▫ outgoing ties: 3.1

• Reciprocity: 20% • E-I index: 0.30 ▫ internal ties: 28 ▫ external ties: 52

PIs PDFs Tr.

PIs 0.30 0.13 0.05

PDFs 0.21 0.50 0.00

Tr. 0.23 0.38 0.14

* Colors denote various laboratories

Co-supervision, lab-placement & the consulting networks?

r = .74

Correlations • with supervision matrix r = .32 (p < .001) • with lab-replacement/co-supervision matrix r = .27 ( p < .001)

Correlations • with supervision matrix r = .43 (p < .001) • with lab-replacement/co-supervision matrix r = .29 ( p < .001)

Acknowledgement

• The authors would like to extend their appreciation to the Natural Sciences and Engineering Research Council of Canada for their financial support.

Comments & feedback

Comparison Matrixes

Primary lab association Enhanced lab association