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4. CONCLUSIONS


From the overall study, we now conclude that there are three significant factors leading to a greater chance for poverty reduction and sustained access of poor and disadvantaged people to mountain natural resources in the long term. They are:

1. Return of democracy: In one way or another, policy processes and development practice are more open to various types of ‘participation’ than ever before. For example, competing narratives are known about and discussed, alternative cultures and behaviours by aid actors are more revealed than ever before.

2. Increased availability and access to information: This has been helped by moves by government, donors and NGOs to become more open and transparent in their work, and by technological changes in the information industry.

3. Increased activity of social entrepreneurs: Social entrepreneurs in the public, private and NGO sectors, including the civil society, are doing more to spread socially responsible institutional and technological innovations in Nepal.

Whether such things are happening elsewhere in the Hindu Kush-Himalayas will require contemporary studies such as this one on access to natural resources, in each country. It would be foolish to generalize without similar studies.

We have argued that it is the practice of projects and programmes that give rise to policy practices and, in particular, that have some of the most profound effects on access by the poor and disadvantaged to mountain natural resources. In our review, we have found a persistence of pipeline thinking at all levels of planning in Nepal - in government, NGOs and the donor sectors. This linear pipeline approach is summarised in Model ‘A’ of Figure 1. The reality in so many cases, however, is that development practice is non-linear, not easily controlled, hence ‘messy’. Model B in Figure 1 represents this situation.

While there is a huge literature that advocates ‘process’ projects and programmes, and process approaches to policy analysis, we have found a persistence of pipeline thinking at all levels. The implications of this are that past programmes and projects have not been managed as well as they might have been, if all partners had agreed to a design reflecting the realities of Model B in Figure 1.

Figure 1. Pipeline vs. Actor Innovation Systems (‘Hard’ Linear vs. ‘Soft’ Messy Systems Compared)[40]

MODEL A

MODEL B

A ‘HARD’ SCIENCE SYSTEMS PERSPECTIVE

The quest for precise linear planning, predictability & control

A ‘SOFT’ SCIENCE SYSTEMS PERSPECTIVE

The reality of messy, fluctuating unpredictability & flexibility

· Traditional ‘pipeline’ model

· New ‘actor-innovation systems’ model

· Central ‘control’ model of policy making and implementation

· Local ‘democratic’ model of policy making and action


[40] With inspirational acknowledgements to Mark Winter and Peter Checkland 2003: 91, Figure 5.

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