This method is considered to be `more objective' because the validator is not biased by the results of the original annotation. This is certainly true for problematic linguistic items like `phonemic categories' or `segment boundaries'. However, this method has also its drawbacks: It is very hard to reconstruct the exact labeling conditions by the validator. You'll need at least one validator in your group that has the skills to do the annotation on the same level as the producer (or even better) and a supervisor who is able to ensure the quality of the annotation. Also, in most cases the inevitable discussion about ``what is to be considered correct'' ensues between the producer and the validator of the speech corpus.
We consider this method to be very effective for the validation of annotations or meta data where the nature of the categorical system is well established and the validator has no problems to justify his/her annotations. These are typically: the gender of a speaker, the transcript, dialog act or word segmentation and simple linguistic and noise tagging. The following data types are considered to be problematic for re-annotation: phonemic, prosodic, syllable, morph segmentation, dialect, age, phrase accent and boundaries.