You have invested an uncountable amount of hours completing your research, and even have been lucky enough (!) with your results confirming the previously stated hypotheses deriving from an extensive literature search. Besides being already happy enough, the next step to consider would be the publication in a journal, the higher the impact factor the better. The hardworking (and fortunate) even complete this enduring step and can rejoice in receiving considerable attention from other scholars in the field. Passionate researchers know what I am talking about. But what about all those researchers that fail to confirm their hypotheses. Do they receive as much attention? The answer to this rhetorical question must presumably be: NO.
Results that are perceived as not advancing our through science constructed knowledge might never reach public attention. This tendency to report almost only positive findings in scientific journals is a common point of contention, especially in the social sciences. Continue reading
Source: Scargle, 2000
“The literature of social sciences contains horror stories of journal editors and others who consider a study worthwhile only if it reaches a statistically significant, positive conclusion; that is, an equally significant rejection of a hypothesis is not considered worthwhile” (Scargle, 2000).
This is a footnote in Jeffrey D. Scargle’s, an astrophysicist working for NASA, article about the publication bias in scientific journals. Usually, the psychologist in me would go all defensive of our precious little social science, but then one discovers this: a couple of researchers trying to publish a paper debunking Bem’s research on ESP (in layman terms, ESP means predicting the future). More precisely, their woes while trying to publish a paper with nonsignificant results. How many papers have you read that have nonsignificant results, that accept the null hypothesis? I have a feeling you have the same answer as me, and it’s frighteningly converging on zero. What happens to those papers? And what’s the implication of such a bias in publishing for science at large?