To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
We illustrate some of the challenges of credit allocation in science by discussing the Thomas theorem –often seen as the orgin of the “self-fulfilling prophecy” – which, ironically given its subject matter, has been repeatedly cited as the work of W. I. Thomas alone. Thomas’ coauthor and wife, Dorothy Swaine Thomas, has never received the credit she deserved for the discovery. This raises this issue of how biases affect credit allocation in science, since our perception of who deserves credit is reinforced by the Matthew effect. We tend to give disproportionate credit to renowned scientists over unknowns, making coauthoring with eminent scientists risky. Many of these problems arise because credit is allocated collectively in science, based on the community’s perception of who is responsible for a discovery. While that perception is often correct, there are plenty of instances where the community gets it wrong. We describe how a collective credit allocation algorithm, which was created using cocitation patterns, can capture how the community assigns credit and predict who will get credit for a discovery. We then discuss the algorithm’s implications for individual scientists.
Email your librarian or administrator to recommend adding this to your organisation's collection.