This study examines how philanthropic foundations develop innovative approaches to grant-making by collaborating with social entrepreneurs who are embedded in marginalized communities. Traditionally, foundations award grants that meet predetermined strategic objectives that support their theories of change. However, this study explores an alternative approach known as participatory grant-making, in which philanthropic foundations cede control over strategy and finance by adopting an innovative approach that is based more on trust and collaboration. By analyzing in-depth interviews from 16 executives, directors, and social entrepreneurs in the United States, we demonstrate how participatory grant-making constitutes a social innovation that inverts traditional power dynamics in the philanthropic field by enhancing legitimacy, and thereby facilitating a more interconnected, inclusive, and equitable approach to solving social problems. This article demonstrates how the implementation of participatory grant-making programs can help to counter the increasing criticisms levied at traditional approaches to grant-making.
BackgroundScientific software incorporates models that capture fundamental domain knowledge. This software is becoming increasingly more relevant as an instrument for food research. However, scientific software is currently hardly shared among and (re-)used by stakeholders in the food domain, which hampers effective dissemination of knowledge, i.e. knowledge transfer.Scope and approachThis paper reviews selected approaches, best practices, hurdles and limitations regarding knowledge transfer via software and the mathematical models embedded in it to provide points of reference for the food community.Key findings and conclusionsThe paper focusses on three aspects. Firstly, the publication of digital objects on the web, which offers valorisation software as a scientific asset. Secondly, building transferrable software as way to share knowledge through collaboration with experts and stakeholders. Thirdly, developing food engineers' modelling skills through the use of food models and software in education and training.
Agent-based modeling is used for simulating the actions and interactions of autonomous entities aiming to assessing their effects on the system as a whole. At an abstract level, an agent-based model (ABM) is a representation of the many simple agents and interactions among them. The decision making of the agents is based on the rules given to them. In an ABM, the model output is the result of internal decision-making and may differ with alteration in the decision path. On the contrary, with the set of rules embedded in agents, their behavior is modeled to take a ‘certain action’ in a ‘certain situation’. It suggests that the internal decision making behavior of agents is truly responsible for the model output and thus it cannot be ignored while validating ABMs. This research article focuses on the validating agents’ behavior by evaluating decision-making processes of agents. For this purpose, we propose a validation framework based on a participatory simulation game. Using this framework we engage a human player (i.e. a domain stakeholder) to allow us to collect information about choices and validate the behavior of an individual agent. A proof-of-concept game is developed for a city logistics ABM to test the framework.
