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The Effects of Co-Supervision and Lab Placement on Social Networks in a Graduate Biology Program
- C. Owen Lo
The Effects of Co-Supervision and Lab Placement on Social Networks - - PowerPoint PPT Presentation
The Effects of Co-Supervision and Lab Placement on Social Networks - - PowerPoint PPT Presentation
The Effects of Co-Supervision and Lab Placement on Social Networks in a Graduate Biology Program Presenter C. Owen Lo Ph.D. Candidate University of British Columbia, Canada Presentation Outline Introduction General Social Network
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Working on Walls (WOW) Proj ect
- 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
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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)
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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?
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Pattern examination of the WOW social interaction
- Cut-point: zero
- 2-step: all nodes
- Core-peripheral index: 0.48
Density m atrix- WoW network Core Peri. Core .8 7 .41 Peri. .41 .20
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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
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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
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Professional development & the general networking
Density PIs PDFs Trs. PIs .75 PDFs .37 1.0 Trs. .53 .83 .93
* Color denotes rank
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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)
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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
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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
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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)
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Acknowledgement
- The authors would like to extend their
appreciation to the Natural Sciences and Engineering Research Council of Canada for their financial support.
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Comments & feedback
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