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skip to content monitoring and evaluation news a news service focusing on developments in monitoring and evaluation methods relevant to development programmes with social development objectives. managed by rick davies, since 1997 menu home about editorial rick’s methods: most significant change (msc) hierarchical card sorting (hcs) evolving storylines……..(es) the basic necessities survey (bns) weighted checklists network visualisation of qualitative data predictive models email lists surveys m&e conferences m&e training forum m&e jobs forum participatory modelling: beginnings of a list what is participatory modelling? gray et al (2018) “the field of pm lies at the intersection of participatory approaches to planning, computational modeling, and environmental modeling” wikipedia: “participatory modeling is a purposeful learning process for action that engages the implicit and explicit knowledge of stakeholders to create formalized and shared representation(s) of reality. in this process, the participants co-formulate the problem and use modeling practices to aid in the description, solution, and decision-making actions of the group. participatory modeling is often used in environmental and resource management contexts. it can be described as engaging non-scientists in the scientific process. the participants structure the problem, describe the system, create a computer model of the system, use the model to test policy interventions, and propose one or more solutions. participatory modeling is often used in natural resources management, such as forests or water. there are numerous benefits from this type of modeling, including a high degree of ownership and motivation towards change for the people involved in the modeling process. there are two approaches which provide highly different goals for the modeling; continuous modeling and conference modeling. recent references gray s, voinov a, paolisso m, et al. ( 2018 ) purpose, processes, partnerships, and products: four ps to advance participatory socio-environmental modeling . ecological applications 28(1): 46–61. doi: 10.1002/eap.1627 . hedelin b, evers m, alkan-olsson j, et al. ( 2017 ) participatory modelling for sustainable development: key issues derived from five cases of natural resource and disaster risk management . environmental science & policy 76: 185–196. doi: 10.1016/j.envsci.2017.07.001 . basco-carrera l, warren a, van beek e, et al. ( 2017 ) collaborative modelling or participatory modelling ? a framework for water resources management. environmental modelling & software 91: 95–110. doi: 10.1016/j.envsoft.2017.01.014 . eker s, zimmermann n, carnohan s, et al. ( 2017 ) participatory system dynamics modelling for housing, energy and wellbeing interactions. building research & information 0(0): 1–17. doi: 10.1080/09613218.2017.1362919 . voinov a, kolagani n, mccall mk, et al. ( 2016) modelling with stakeholders – next generation . environmental modelling and software 77: 196220. doi: 10.1016/j.envsoft.2015.11.016 . share this: email print twitter facebook linkedin reddit google skype tumblr like this: like loading... author rick davies posted on 12 june, 2018 categories participatory modelling leave a comment on participatory modelling: beginnings of a list computational modelling of public policy: reflections on practice gilbert g, ahrweiler p, barbrook-johnson p, et al. (2018) computational modelling of public policy: reflections on practice. journal of artificial societies and social simulation 21: 1–14. pdf copy available abstract: computational models are increasingly being used to assist in developing, implementing and evaluating public policy. this paper reports on the experience of the authors in designing and using computational models of public policy (‘policy models’, for short). the paper considers the role of computational models in policy making, and some of the challenges that need to be overcome if policy models are to make an effective contribution. it suggests that policy models can have an important place in the policy process because they could allow policy makers to experiment in a virtual world, and have many advantages compared with randomised control trials and policy pilots. the paper then summarises some general lessons that can be extracted from the authors’ experience with policy modelling. these general lessons include the observation that ofen the main benefit of designing and using a model is that it provides an understanding of the policy domain, rather than the numbers it generates; that care needs to be taken that models are designed at an appropriate level of abstraction; that although appropriate data for calibration and validation may sometimes be in short supply, modelling is ofen still valuable; that modelling collaboratively and involving a range of stakeholders from the outset increases the likelihood that the model will be used and will be fit for purpose; that attention needs to be paid to effective communication between modellers and stakeholders; and that modelling for public policy involves ethical issues that need careful consideration. the paper concludes that policy modelling will continue to grow in importance as a component of public policy making processes, but if its potential is to be fully realised, there will need to be a melding of the cultures of computational modelling and policy making. selected quotes : for these reasons, the ability to make ‘point predictions’, i.e. forecasts of specific values at a specific time in the future, is rarely possible. more possible is a prediction that some event will or will not take place, or qualitative statements about the type or direction of change of values. understanding what sort of unexpected outcomes can emerge and something of the nature of how these arise also helps design policies that can be responsive to unexpected outcomes when they do arise. it can be particularly helpful in changing environments to use the model to explore what might happen under a range of possible, but dfferent, potential futures – without any commitment about which of these may eventually transpire. even more valuable is a finding that the model shows that certain outcomes could not be achieved given the assumptions of the model. an example of this is the use of a whole system energy model to develop scenarios that meet the decarbonisation goals set by the eu for 2050 (see, for example, raeng 2015.) rick davies comment : a concise and very informative summary with many useful references. definitely worth reading! i like the big emphasis on the need for ongoing collaboration and communication between model developers and their clients and other model stakeholders however, i would have liked to see some discussion of the pros and cons of different approaches to modeling e.g. agent-based models vs fuzzy cognitive mapping and other approaches. not just examples of different modelling applications, useful as they were. see also: uprichard, e and penn, a (2016) dependency models: a cecan evaluation and policy practice note for policy analysts and evaluators. cecan. available at: https://www.cecan.ac.uk/sites/default/files/2018-01/emma%20ppn%20v1.0.pdf (accessed 6 june 2018). share this: email print twitter facebook linkedin reddit google skype tumblr like this: like loading... author rick davies posted on 11 june, 2018 categories journal article leave a comment on computational modelling of public policy: reflections on practice representing theories of change: technical challenges and evaluation consequences cedil – centre for evaluation lecture series the centre of excellence for development impact and learning ( cedil) and the centre for evaluation host a lecture series addressing methods and innovation in primary studies. watch the live-streamed lecture here london school of hygiene and tropical medicine. lecture two – wednesday 30th may 2018 – dr rick davies 12:45-14:00 jerry morris b, l

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