Given Hapunda

125 Funding and Funders All development work or ‘doing’ development requires money and that includes monitoring and evaluation activities. In any case, even research that is purely academic might require a sponsor. Ethical issues therefore arise when the results from the evaluation are not in line with the views of the funders (Lemmens & Freedman, 2000). This raises a dilemma for the evaluation officer because publishing such results could entail the termination of the project- closing any further access to funding from such sponsors, which may ultimately hinder the organisation’s future work and could have far-reaching impacts on personal career development. The dilemma is, do you publish and ‘perish’ or do you develop short term amnesia on the aspects of your findings/outcomes that are not favourable to your organisation and the funders? Or do you manipulate the data so that the problematic aspects are no longer a problem? (See, Lundh et al ., 2015). From an ethical point of view, falsifying the results is never an answer nor is developing short termmemory lapses. In an event that you get unexpected results, it is prudent to do a thorough check at community level as this could entail some lapses during the monitoring and evaluation process which could be worked out. In other cases, however, it could help initiate alternative thinking or ways of doing things which could be beneficial to the project and its recipients (Brydon, 2006). Responsibilities and Competence Clarification of responsibilities and competence in M&E can help reduce ethical problems. For instance, clarifying responsibilities helps ensure that work is undertaken systematically and competently, with integrity, honesty and respect for people, local values and cultural norms. The goal is to promote honesty, justice and development to improve the quality of life of those being served (Hagens, 2008). The M&E staff must engage in systematic inquiry that meets the highest standards for each activities of the M&E component undertaken. This involves but not limited to: 1. Acknowledging and attempting to eliminate bias in M&E activities. Biasness may result from poor methodologies, for example, data collection measures that are not valid or reliable. It may also involve staff collecting data from the sample that was not defined in the evaluation design in the first place. See exhibit box below (Focus Box.2).