Gea Galluzzi, Bioversity and Aseffa Wedajoo, University of Illinois-Chicago: “Policy Network Analysis to support national implementation of the International Treaty on Plant Genetic Resources for Food and Agriculture” Workshop on Approaches and Methods for Policy Process Research, co-sponsored by the CGIAR Research Programs on Policies, Institutions and Markets (PIM) and Agriculture for Nutrition and Health (A4NH) at IFPRI-Washington DC, November 18-20, 2013.

1. Policy Network Analysis to support
national implementation of the
International Treaty on Plant Genetic
Resources for Food and Agriculture
Gea Galluzzi, Aseffa Seyoum, Richard Ogwal

2. Outline
Context
Objectives
Theories, tools and methods
Results from East Africa

3. The context

4. The International Treaty on PGRFA
•
•
Common framework for conservation and sustainable use
Multilateral system of access and benefit-sharing (MLS)
Status: into force in 2004; 130 ratifications
Implementation
Few countries have developed the mechanisms to
participate proactively in the MLS. Why???
•
•
•
Little knowledge or engagement
Isolation, lack of coordination among relevant agencies
…..

5. Genetic Resources Policy Initiative (phase 2) – GRPI2
Building capacities for implementing the International Treaty and its
Multilateral System
8 countries (Asia, Africa, Latin America)

6. Objectives, theories
and methods

7. Research component on policy networks
•
Gather empirical evidence on who are relevant actors, (existing or missing)
connections, directions of information, influences
•
Identify interventions to create or strengthen connections and stakeholder
engagement
Inform national policy-making processes
for IT and MLS implementation
Collaboration between Bioversity International, the Science, Technology and Environment Policy (STE) Lab
at the University of Illinois at Chicago and teams of national research partners from each country

8. Theories and frameworks - Social Network Analyses (SNA)
Network: a set of dyadic ties all of the same type, among a set of actors.
Networks are everywhere!
Special kind of data = relationships!
Assumptions
•
People influence each other
•
Energy, resources and information flow through relationships
•
Individual characteristics are only part of the story
•
….

9. Methods - Data collection
Survey (3 languages)
Snowball sampling approach
Face to face interviews recorded in SSI Web CAPi tool
•
•
•
Methods - Data analyses
•
14
12
•
10
8
6
4
2
0
•
Statistical analyses of traditional survey data
(perceptions, knowledge)
Analysis of network data (relations, connections)
Results and network map interpretation with national
project partners

10. Results in Uganda
and Rwanda

11. … Preliminary findings…
 Number of respondents: Uganda - 26; Rwanda - 37
 Variety of different actors (organizations) involved

In Uganda, out of actors currently involved in the ITPRGFA policy
network,
 International (32%),
 National governmental (15%),
 Private sectors and farmers organizations, about 11%
 …
 There are actors not involved but should be involved
 In Uganda, about 66% of the organization recommended to
be involved in the IT are either national or regional
 Inconsistency in identifying actors who are [not] involved

12. … Preliminary findings…

The survey asked actors perspectives about the ITPGRFA and
the MLS


Most respondents about 68% for Uganda and about 73% believe that
the IT is very beneficial for their country
In both countries the main constraints on implementation
 Financial and capital resources constraint
 Lack of sufficient information, and
 Lack of legal and policy expertise, particularly in Rwanda

13. … Preliminary findings…
 IT/MLS actors involved in many other national policy networks
 Biosafety,
 Phytosanitary,
 Plant Variety Protection (PVP)
 CBD, seed policy, etc.
 IT policy network in Uganda is centralized while that of Rwanda in
more decentralized
 Resource exchange networks- vary substantially across networks
and countries
 Science networks are more connected
 Policy advice, legal, financial resource networks are more
limited with only a few key actors

14. … Preliminary findings…
Table 1. Network Metrics (Uganda)
Number of
ties
Number of
nodes
Centralization
(outdegree,%)
Density
Average
degree
centrality
All relationships
196
95
60.1
0.022
2.1
Legal expertise
79
50
22.8
0.009
0.8
Policy and
administrative direction
135
65
26.4
0.015
1.4
Scientific expertise
218
81
55.6
0.024
2.3
Financial resources
64
45
14.3
0.007
0.7
Table 3. Network Metrics (Rwanda)
539
175
Number of
connected
nodes
94
61
130
293
79
63
73
47
Number of
ties
All relationships
Legal expertise
Policy and administrative
direction
Scientific expertise
Financial resources
Centralization
(outdegree,%)
Density
34.45
19.34
0.059
0.019
Average
degree
centrality
5.62
1.82
14.52
31.86
8.70
0.014
0.032
0.009
1.35
3.05
0.82

15. … Preliminary findings
Communication network:

Frequency of communication and structural hole
 NARO and BI; FAO and MAAIF
Uganda

FAO and MAARI; MAAR and MINAGRI
Rwanda

16. … Preliminary findings
ITPGRFA Implementation Priority Network
 NAAR
 KakinduFC
Uganda
 MAAR
Rwanda

17. Ways forward
Further research


Better understand how key actors characteristic affect IT policy
implementation
Further assess the effect of policy actors network dynamism (inclusion and
exclusion of actors) on the policy process
Towards implementation

Capacity building and communication with and within network
(workshops, publications, briefs)

Inclusion of actors not currently involved but should be involved (form or
strengthen national commission on PGRFA)

Dissemination of results of on-going research on
incentives, disincentives, opportunities and needs of country participation in
the IT/MLS

18. Thank you
www.bioversityinternational.org

19. Additional
information

20. … Preliminary findings…
Table 1. Selected national polices in which ITPGRFA actors are involved
Polices
Access and Benefit Sharing Policy
Biosafety Policy
Convention on Biological Diversity
Environment Policy
Farmers' Rights
Phytosanitary Policy
Plant Breeders' Rights
Seed Policy
Trade and Investment Policy
Plant Variety Protection (PVP)
UgandaN. ITPGRFA
policy actors
involved
6
15
2
4
11
9
5
4
4
RwandaN. ITPGRFA
policy actors
involved
9
17
2
6
10
10
12
1
8
2

21. All relationships
•
NARO, MAAIF, Makerere Uni., BI
Uganda
•
CRS, RAB, INGABO, BI
Rwanda

22. … Preliminary findings
Table 4. Actor Type and Involvement in ITPGRFA Policy Implementation (Uganda)
Type of organization
International
Regional
National government
National NGOs
Provincial/county govt.
Farmers organizations
Private sector
Others (university, media)
Total
Status of involvement
Involved
Not Involved
n
Percent
n
Percent
32
33.7
2
11.1
7
7.4
6
33.3
14
14.7
6
33.3
5
5.3
1
5.6
5
5.3
0
0.0
10
10.5
0
0.0
10
10.5
1
5.6
12
12.6
2
11.1
95
100.0
18
100.0
Total
n
34
13
20
6
5
10
11
14
113
Percent
30.1
11.5
17.7
5.3
4.4
8.8
9.7
12.4
100.0
Table 5. Actor Type and Involvement in ITPGRFA Policy Implementation (Rwanda)
Type of organization
International
Regional
National government
National NGOs
Provincial/county govt.
Farmers organizations
Private sector
Others (university, media)
Total
Status of involvement
Involved
Not Involved
n
Percent
n
Percent
29
30.85
1
9.09
11
11.70
0
0
15
15.96
3
27.27
7
7.45
1
9.09
2
2.13
0
0
9
9.57
1
9.09
11
11.70
1
9.09
10
10.64
4
36.36
94
100
11
100
Total
n
30
11
18
8
2
10
12
14
105
Percent
28.57
10.48
17.14
7.62
1.90
9.52
11.43
13.33
100

23. Methodological challenges
•
PNA is a well established techniques that has been used
to analyze policy-making and implementation
•
Some of the challenge - related to data collection



it is data intensive technique
arranging interview with policy actor is not easy
some of the policy related questions in the survey might be
sensitive for respondents