As we answer to be valued by algorithms at work

As we answer to be valued by algorithms at work

Quick summary:

1. For example, highly estimated freelancers, which also have a large number of their revenues from the platform, have largely influence any recent falls in their assessment, with those freelancers, striving to experiment, to try to return their account to their former status.

2. When the researcher first joined the platform, the rating system was rather transparent, in the fact that freelancers were rated on the estimates given for projects, with higher values ​​of the projects gave more weight in determining their total score.

3. What I am most surprised that the highest performers and most experienced freelancers on the platform did not have any advantages from the point of view of finding out how the algorithm worked, the researcher says

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