| Abstract: |
Science is often said to bar dishonesty and bad research with a triple safety net. The first is peer review, in which experts advise funders about what research to finance. The second is the referee system, which has journals ask reviewers to judge if manuscripts merit publication. The last is replication, whereby independent scientists see if the work holds up.
Even the most prestigious scientific journals, with the most rigorous systems of peer review, have had the unpleasant experience of having to withdraw publications on ‘new’ findings, that were based on falsified or dubious data. For example, the journal Science (Volume 289, 18 August 2000) retracted a paper previously published by the journal after it was found that one of the authors had falsified data. The significance of this is discussed in a thoughtful piece by Donald Kennedy in the same issue (p1137). He makes the point that every case of this type damages the reputation not only of the people and institutes involved, but, in the eyes of our public patrons, science and scientists generally. The Science case is not unique. A laboratory in Europe has recently had to retract hundreds of papers and around the world there are numerous cases being
investigated.
Within ICRAF, and in many of our partner institutes, there seem to be two contradictory experiences. On the one hand there is the view that scientific fraud - the deliberate use of false data with intention to mislead – does not happen in serious scientific institutes. Apart from a few well-publicized cases (cigarette damage, Piltdown Man, stem cells, perhaps cold fusion), basic scientific ethics would prevent anyone from deliberately fabricating evidence. On the other hand many scientists have had personal experiences in which they discovered or strongly suspected that data had been falsified. However, if these cases are not openly discussed, the correct reaction of the institute is not understood and there is no discussion of the reasons for fraud occurring nor putting in place mechanisms and systems to reduce likelihood of future fraud. |
|
