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DOL Funding 19 States’ Contractor Status Attacks

Volume 2, Issue 18
September 30, 2014
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The Department of Labor is funding 19 states’ enforcement programs aimed at businesses unwittingly or intentionally failing to make unemployment contributions for individuals misclassified as independent contractors.

The funds are intended to increase the ability of state unemployment insurance tax programs to identify instances where employers improperly classify employees as independent contractors or fail to report wages paid to workers.

The states selected for grants will reportedly use the funds for improvements and initiatives that include enhancing employer audit programs and conducting employer education initiatives.

A single claim by one worker can lead to the administrative equivalent of a class action for independent contractor misclassification, warn attorneys for the law firm of Pepper Hamilton LLP.

“An audit and an unemployment claim can lead to the equivalent of an administrative class action, where an unemployment agency finds a single individual to be an employee instead of an independent contractor and orders the business to remit contributions for the employee ‘and all similarly-situated employees,’” they note.

These proceedings can, in turn, lead to follow-up regulatory challenges by state workers’ compensation agencies, state tax commissioners, state wage and hour divisions, and of course the IRS and the U.S. Department of Labor – or a plaintiffs’ class action lawyer seeking an array of damages.

The 19 states that received the grants totaling $10.2 million were California, Delaware, Florida, Hawaii, Idaho, Indiana, Maryland, Massachusetts, New Hampshire, New Jersey, New Mexico, New York, Oregon, South Dakota, Tennessee, Texas, Utah, Vermont, and Wisconsin.

Four states received “high-performance bonuses” totaling over $2 million: Maryland, New Jersey, Texas, and Utah. Labor Secretary Thomas Perez said these bonuses reward states with additional grant funds “due to their high performance or most improved performance in detecting incidents of work misclassification.”

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