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Uber Technologies Inc. has filed a brief asking the Ninth Circuit Court to reverse or vacate employee misclassification lawsuits that were expanded by U.S. District Judge Edward M. Chen in late 2015.
Uber’s consolidated appeal addresses four class action lawsuits that are moving through the court system. Uber prefers the cases be settled through arbitration. The Uber employee misclassification cases are considered high-profile class actions and include the O’Connor, Yucesoy, Mohamed and Del Rio cases.
“Throughout this litigation, the district court has issued a series of anti-arbitration and pro-class-certification orders that have wreaked havoc on Uber’s relationship’s with drivers. The district court began by invalidating, then ordering Uber to rewrite – and then invalidating again – millions of arbitration agreements, which require drivers to arbitrate any disputes they may have with Uber on an individual basis,” said Uber in its submitted paperwork.
Uber Wants Employee Misclassification Issue to Enter Arbitration
In December 2015, Judge Chen decided the O’Connor case could expand a class of drivers that had been certified in September 2015 to add a subclass of 240,000 Uber drivers who had accepted arbitration agreements that included class action waivers. Judge Chen also addressed a claim for expense reimbursement even though the initial claim had addressed tips only.
“With each order, the district court has encouraged as many drivers as possible to opt out of arbitration and join the class actions pending against Uber, all the while bending and breaking the requirements of Rule 23, the Federal Arbitration Act and due process,” Uber contested. “This court should reverse these incorrect rulings, decertify the class and enforce the arbitration agreements.”
The Ninth Circuit said Judge Chen went beyond the bounds of his authority when he determined the enforceability of 2013 and 2014 Uber driver agreements. As a result, the Ninth Circuit reinstated the original arbitration agreements in the Mohamed case and in an unrelated Uber case, Gillette v. Uber.
Uber insists that its arbitration agreements should be honored because they are valid. They also argue that Judge Chen ignored the fact that multiple individual interrogations would be necessary to determine whether or not Uber participates in employee misclassification.
Uber drivers want Judge Chen’s orders to remain in effect because they believe the class action waivers violate their rights under the National Labor Relations Act.
Shannon Liss-Riordan of Lichten & Liss-Riordan PC is the lead attorney for the Uber drivers. Liss-Riordan told Law360: “We do not believe that Uber can or should be able to use its arbitration clause to avoid the repercussions of its systemic misclassification of its drivers across the state and resulting wage violations.
“Moreover, the district court issued a very thoughtful and well-reasoned order granting class certification,” Liss-Riordan continues. “As for the Rule 23(d) orders, those are basically moot at this point, and Uber’s continued appeal of those orders simply shows that it wants to try to complicate this litigation as much as it can in order to try to distract from the real issues at hand.”
Two of the employee misclassification lawsuits were nearly settled for $100 million. The O’Connor and Yucesoy cases saw the proposed deal struck down by Judge Chen in August 2016 because he did not believe it was structured appropriately or adequately to cover the potential claims.
The Employee Misclassification Lawsuits involved in the consolidated appeal are Douglas O’Connor, et al. v. Uber Technologies, Inc., Case Nos. 1416078, 1517420, 1517532, 1615000, and 1615595; Hakan Yucesoy et al. v. Uber Technologies Inc., Case Nos. 1517422, 1517534, and 1615001; Abdul Mohamed et al. v. Uber Technologies Inc., Case Nos. 1517533 and 1615035; and Ricardo Del Rio et al. v. Uber Technologies Inc., Case No. 1517475, all in the U.S. Court of Appeals for the Ninth Circuit.
UPDATE: May 2019, the Calif., Mass., Uber driver misclassification class action settlement is now open. Click here to file a claim.
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