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Notes 1 Working on Walls (WoW) – an NSERC CREATE Training Program University of British Columbia Vancouver, Canada Social Network Analysis December 2012.

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Presentation on theme: "Notes 1 Working on Walls (WoW) – an NSERC CREATE Training Program University of British Columbia Vancouver, Canada Social Network Analysis December 2012."— Presentation transcript:

1 Notes 1 Working on Walls (WoW) – an NSERC CREATE Training Program University of British Columbia Vancouver, Canada Social Network Analysis December 2012 By C. Owen Lo & Arwa Alkhalaf

2 Notes 2 Executive Summary Overall Network Complexity Development The response rate over the course of the 2012 surveys was 96% (A survey was sent in September 2012 and 62% of the Trainees completed the survey; however due to some technical glitches, the data was not analyzable, so the survey was re-distributed in December Due to low response rate the December 2012 survey was re-sent in February 2012). All non-sabbatical WoW members responded to the survey except on PI. The overall WoW social network is fairly active. Among all survey respondents (n=23), a total number of 311 outgoing ties were indicated. On average, each survey participant had 13.1 outgoing ties (the range of actual outgoing ties numbered from ). More people outside of the WoW context were indicated in this final survey – a difference from previous years. In total 17 participants (including 5 PIs, 3 PDFs, and 9 Trainees) listed 56 ties linked to 42 external individuals as part of their academic professional networks. As part of their professional (non-academic) networks, 13 ties linked to 12 individuals were indicated by 5 Trainees (including 3 PIs, 1 PDF, and 1 Trainee). The increase in external connections could be attributed to the fact that there was an international symposium organized by this project group in The connections developed, or were increased by hosting international students and scholars. Since many of the Trainees took part in organizing and participating in the 2011 WoW symposium, many of the external ties made then continued and were mentioned in this survey (e.g., Y. Watanabe mentioned 5 external ties to the Nara Institute of Science and Technology (NAIST) in Japan). There were four WoW workshops to discuss career options where new connections may have been developed. Research-Related Supervision & Mentoring All of the Trainees in the survey (n=13) consulted with their designated supervisors during the time period. Seventy percent of these Trainees also indicated that they consulted with their designated co-supervisors. PDFs who participated in this survey only indicated consultation with their designated supervisors. Overall, WOW Trainees indicated at least two colleagues with whom they had contact for research-related issues. The average number of out-going consultation ties for the survey respondents was 5.3. Although the sample size was too small for a statistical test, the number of connections a Trainee has seems to correlate to a Trainee’s seniority (see Appendix E).

3 Notes Question 1: Which of the following Trainees have you had connections with in the past 6 months? 3 Overall Network – A General Look Density: 0.59, # of Ties: 311 Reciprocity = 0.56 All nodes can reach another with a path shorter than two steps This map displays the general social interactions among Trainees. In total, 311 ties were indicated by 23 WoW members (including a program manager) and 56% of these ties were indicated as reciprocal. The network as a whole was rather coherent with a density value of 59%. While this social map displays the internal interactions, external connections were determined by asking two other questions. In total, 42 people were identified by the Trainees as part of their academic professional network (see Appendix A) while 13 people were identified by the Trainees as part of their non- academic professional network (see Appendix B). P = PI D = PDF T = Trainee M= Manager Blue lines = Reciprocal lines

4 Notes 4 Overall Network – Density Density: 0.57, # of Ties: 274 PIs: 0.81 PDFs: 0.67 Trainees: 0.62 Reciprocity: 0.55 PIs: 0.54 PDFs: 0.50 Trainees: 0.67 The existing ties account for 57% (# = 274) of the possible ties within this network. Thirty- eight percent of these existing ties are reciprocal. As outlined, members with similar academic ranks (PIs, PDFs, Trainees) tend to have stronger affiliations to each other. Note, the manager was removed from this map in order to better demonstrate the interaction between Researchers. The following table demonstrates the inter- and intra-group (read as row to column) densities. DensityTrPDFPI Tr PDF PI Question 1: Which of the following Trainees have you had connections with in the past 6 months?

5 Notes Question 1: Which of the following Trainees have you had connections with in the past 6 months? 5 Overall Network – In-degree Range: 4-20, Average: 12.9, SD: 3.76 PIs: 13.3 PDFs: 15.7 Trainees: 12.1 Q1 In-degree table The size of a node demonstrates the number of incoming ties that a Trainee indicated (the lareger the node, the more incoming ties.) M. Schuetz had the highest value among all Trainees although he did not participate in the December 2012 survey. PDFs, as a group, had the highest average network. The table below illustrates the number of Trainee’s incoming ties. D320 T513 P119 T913 P217 T712 T817 T212 D216 D411 P615 T311 P314 T1210 T114 T139 T614 P48 T1114 P57 T1014 T144 P813

6 Notes Question 1: Which of the following Trainees have you had connections with in the past 6 months? 6 Overall Network – Out-Degree Range: 4-22 Average: 13.1 SD: 5.63 PIs: 13.3 PDFs: 8 Trainees: 14.2 The size of a node displays the number of outgoing ties that a Trainee indicated. B. Ellis (Project Leader) had the highest value in the network. Trainees as a group, had the highest average. The table below illustrates the number of Trainee’s outgoing ties. Q1 Out-degree table P122T614 T521P613 T1220T1110 T320T1010 T920P59 T218T79 T116P47 P315D46 T815T146 P214T135 D314D24

7 Notes Question 2: Whom do you ask for help when you have a challenging problem and/or an innovative idea in your research? Consultation Network – Density & Reciprocity Density: 0.19, # of Ties: 94 PIs:.47, PDFs: 0.33, Trainees: 0.08 Reciprocity: 0.32 PIs: 0.48, PDFs: 0.27, Trainees: TrPDFPI Tr PDF PI ties were indicated by 22 respondents (exclude the project manager). The 13 Trainees who participated in this survey indicated 23 outgoing ties with the PIs and 17 outgoing ties with the PDFs. On average, a Trainee reported 3.4 outgoing ties to the PIs and PDFs. The table below indicates that when PIs encounter problems, they most likely solicited information from other PIs and PDFs; PDFs mostly likely would go to other PDFs; whereas Trainees approached the PDFs. Q2 density table Note: Blue lines are reciprocal lines

8 Notes 8 The size of a node indicates the number of incoming ties a Trainee received in regards to obtaining help with challenging problems. PDFs as a group had the highest average (8.7 ties) of this measure. In the map, Trainees with more seniority tended to have more incoming ties. Consultation Network – In Degree Range: 0 – 11, Average: 4.1, SD: 3.58 PIs: 6.3 PDFs: 8.7 Trainees: 1.8 Q2 In Degree table Note: Blue lines are reciprocal lines Question 2: Whom do you ask for help when you have a challenging problem and/or an innovative idea in your research? D311T63 P210P42 P69T12 D29T132 P18T22 P88T31 D46T140 T56T70 P34T120 T84T110 T94T100 P53

9 Notes 9 The size of a node indicates the number of outgoing ties a Trainee indicated when asked to whom they consulted with challenging problems within the WoW context. Consultation Network– Out-Degree (internal) Range: 1-9, Average: 4.3, SD: 2.59 PIs: 5.5 PDFs: 2.7 Trainees: 4.1 Q2 Out-degree table (within WoW) Note: Blue lines are reciprocal lines Question 2: Whom do you ask for help when you have a challenging problem and/or an innovative idea in your research? T69T124 P28P53 P18P33 T98D22 T37T72 P66T82 T56T112 P45T102 D35D41 T15T141 T134T21

10 Notes 10 The size of a node indicates the number of outgoing ties a Trainee indicated in regard to consulting challenging problems. Appendix C gives more detailed information on the triangle-shaped nodes (non- Trainees) in the map. In Appendix D, the nodes are coloured according to the primary lab in which a Trainee works. Consultation Network – Out-degree (all) Range: 1 – 13, Average: 5.3, SD: 3.17 PIs: 6.3 PDFs: 3.7 Trainees: 5.2 Q2 Out-degree table (with others) Note: Blue lines are reciprocal lines Question 2: Whom do you ask for help when you have a challenging problem and/or an innovative idea in your research? T913T135 T611T125 P19P33 P28D43 T38T143 P67T73 T57D22 P56T82 D36T112 P45T102 T15T21

11 Notes 11 When asked to whom they made connections with from outside of the WoW group for professional academic issues, 56 ties to 42 people were named by 17 Trainees. UPSC = Umea ̊ Plant Science Centre, Umea, Sweden NAIST = Nara Institute of Science and Technology, Nara, Japan MPI = Max Planck Institute of Molecular Cell Biology and Genetics MSL = Michael Smith Laboratories, UBC, BC UBC = University of British Columbia, Vancouver, Canada MRU = Mount Royal University, Calgary, Alberta IBMP CNRS = Biologie Moléculaire des Plantes, Centre national de la recherche scientifique, Strasbourg, France UofT = University of Toronto, Toronto, Canada UVIC = University of Victoria, Victoria, Canada NUI = National University of Ireland, Galway UC = University of California CCRC = Complex Carbohydrate Research Center, Athens, Georgia Appendix A Information on the professional network (academic) outside of the WoW context NamePositionNotes Bjorn SundbergProfessorUPSC, Sweden Taku DemuraProfessorNAIST, Japan Kerstin Müller John Page Uni. of Calgary Staffan Persson MPI, Germany Alexandra TauzinPDFMSL, UBC Olivier HamantProfessorU of Lyon, France Mellissa Roach UBC PDF Thomas GrigliattiProfessorUBC Yoshito OgawaDoctoral StudentNAIST, Japan Jane Parker MPI, Germany Arata YonedaAssistant ProfessorNAIST, Japan Qingning Zeng previous PhD in the lab Faride Unda PDF, UBC Stefan JanssonProfessorUmea, Sweden Rosie RedfieldProfessorUBC Michael FriedmannLab ManagerDouglas Lab, UBC Dr. David BirdProfessorMRU, Calgary Daniele Werck- ReichhartResearch DirectorIBMP, Strasbourg Patrick von AderkaasProfessorUVic Barbara HawkinsProfessorUVic NamePositionNotes Chris Somerville UC Berkeley David P. LatorreGrad StudentUni. of Alberta Yoshimi NakanoPDFNAIST, Japan Zander MyburgProfessorUni. of Pretoria, SA Anna PielachPDFGalway, NUI Eliana Gonzales- Vigil PDF, UBC Lise JouaninVersaille, INRA Hitoshi EndoDoctoral StudentNAIST, Japan Debra Mohnen Professor CCRC, Uni. of Georgia Bo XuPDFNAIST, Japan Hannele TuominenProfessorUPSC, Sweden Diyana RejabDoctoral StudentNAIST, Japan Daniel MattonProfessorUni. of Montreal Natasha WordenDoctoral StudentUC Davis Keiko YoshiokaProfessor Marcus SamuelProfessorUni. of Calgary Ralf ReskiProfessorFreiburg, Germany Lukas SchreiberProfessorBonn, Germany Peter ConstabelProfessorUVic Nicholas ProvartProfessorUofT

12 Notes 12 Appendix B When asked to whom they made connections in the non- academic professional network outside of the WoW group, 12 people were named by 5 Trainees (research fellows only). Of note, the Program Manager named 8 other people to her non-academic professional network (not included in the table). Information on the professional network (non-academic) outside of the WoW context NamePositionNotes Ellie GriffithProgram managerGenome BC Ashleen ShadoResearch program managerGenome BC Meilin Yi ZinkGreen house manager Kris PalamaTechnical support New England Biolabs, Career Choices Workshop Christopher RoachGrad studentUBC Min XiaGrad studentUBC LindsayGrad studentUBC Vicky EarlGraphic designerUBC media group Jessica PageResearch AccountingUVic Sean MylesProfessor Lead Organizer - Canadian Plant Genomics Workshop 2013, Halifax Alison DendoffCoordinatorGenome BC Sandy BlightResearch AccountingUniv. of Victoria

13 Notes 13 Appendix C The table lists people with whom Trainees indicated they contacted for help with a challenging problem and/or an innovative idea in their research. 22 outgoing ties which connected to 18 non- Trainees were indicated by 13 WoW members. UBC = University of British Columbia, Vancouver, Canada FAFU = Fujian Agriculture and Forestry University, Fuzhou City, Japan NAIST = Nara Institute of Science and Technology, Nara, Japan UofT = University of Toronto, Toronto, Canada IBMP CNRS = Biologie Moléculaire des Plantes, Centre national de la recherche scientifique, Strasbourg, France Information on ‘others’ for Q2 NamePositionNotes Dr. Bjorn SundbergProfessorUPSC Heather McFarlaneDoctoral studentUBC Dr. Chris AmbroseResearch AssociateUBC Dr. Alexandra TauzinPDFUBC Dr. Sylwia WajosPDFWasteneys lab, UBC Dr. Minsheng YouProfessorFAFU, China Dr. Arata YonedaAssistant professorNAIST Yuan RuanDoctoral studentWasteneys lab, UBC Dr. Yoshimi NakanoPDFNAIST Dr. Taku DemuraProfessorNAIST Hitoshi EndoDoctoral studentNAIST Dr. Wnzislawa CkurshumovaPDFUofT Dr. Peter ConstabelProfessorUVic Dr. Patrick von AderkaasProfessorUVic Dr. Barbara HawkinsProfessorUVic Dr. Kevin HodgsonMicroscopy technicianUBC Dr. Daniele WerckDirector of a research groupIBMP CNRS Strasbourg, France Dr. Hugues RenaultProfessorIBMP CNRS Strasbourg, France

14 Notes 14 Appendix E Ego network – P1 General networkConsultation network

15 Notes 15 Appendix E Ego network – P2 General networkConsultation network

16 Notes 16 Appendix E Ego network – P3 General networkConsultation network

17 Notes 17 Appendix E Ego network – P4 General networkConsultation network

18 Notes 18 Appendix E Ego network – P5 General networkConsultation network

19 Notes 19 Appendix E Ego network – P6 General networkConsultation network

20 Notes 20 Appendix E Ego network – D2 General networkConsultation network

21 Notes 21 Appendix E Ego network – D3 General networkConsultation network

22 Notes 22 Appendix E Ego network – D4 General networkConsultation network

23 Notes 23 Appendix E Ego network – T1 General networkConsultation network

24 Notes 24 Appendix E Ego network – T2 General networkConsultation network

25 Notes 25 Appendix E Ego network – T3 General networkConsultation network

26 Notes 26 Appendix E Ego network – T5 General networkConsultation network

27 Notes 27 Appendix E Ego network – T6 General networkConsultation network

28 Notes 28 Appendix E Ego network – T7 General networkConsultation network

29 Notes 29 Appendix E Ego network – T8 General networkConsultation network

30 Notes 30 Appendix E Ego network – T9 General networkConsultation network

31 Notes 31 Appendix E Ego network – T10 General networkConsultation network

32 Notes 32 Appendix E Ego network – T11 General networkConsultation network

33 Notes 33 Appendix E Ego network – T12 General networkConsultation network

34 Notes 34 Appendix E Ego network – T13 General networkConsultation network

35 Notes 35 Appendix E Ego network – T14 General networkConsultation network


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