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Short abstract:

Promising in science fosters cooperation but often leads to broken promises due to uncertainty and incentives to overpromise. Despite awareness, these practices persist, fueling hype and disappointment. I propose a query to track promises to understand why these issues are not corrected over time.

Long abstract:

One prominent activity contributing to hype is that of promising. Promising is a regular and often expected feature of the scientific endeavour, and with good reason – promising enables mutual confidence and makes cooperation possible. However, due to the inherent uncertainty of science, promises are often broken. In addition, scientists have much to gain in the short term by overpromising. These two factors combined lead to a high rate of broken promises in science.

Even though both scientists and funders seem aware of the prevalence of broken promises, current practices seem to continue unabated. The expectations following promises continue to contribute to the emergence of hype, with broken promises contributing to the almost inevitable disappointment following long periods of hype. I therefore propose the empirical, longitudinal study of promises, to better understand why problematic promising practices are not corrected over time. I present preliminary results of the development and application of a search query which allows users to search for predictions in a given corpus. For each prediction, the date when the prediction was made and other relevant metadata are given. The user can subsequently manually determine whether a prediction was a promise or not and, in combination with the metadata, analyse when a promise first arose and how it developed over time. This lays the foundation for further analysis of whether unrealistic promises are corrected over time and if not, which mechanisms are in place that incentivize exaggerated promises.