Bayes Impact Manager • over 8 years ago
White House & US Department of Labor - Predicting Underpaying Employers
Partner
US Department of Labor
Challenge Questions
Can we predict employers that are mostly likely to under-pay their employees? Combine Wage and Hour (WHD) data, Migrant and Seasonal Agricultural (MSHA) and Wage and Hour Compliance to predict the likelihood of being a bad employer.
Data
Wage Hour Division (WHD) Compliance Action Data: http://ogesdw.dol.gov/views/data_summary.php
OFCPP & MSHA Compliance Data: http://ogesdw.dol.gov/views/data_catalogs.php
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3 comments
Tyrone Grandison • over 8 years ago
The DOL team is monitoring this thread. Please place all questions here.
Migrant & Seasonal Agricultural Data http://www.dol.gov/whd/regs/statutes/FLCList.htm
Cody Wild • over 8 years ago
Question: Do you have access to any other data that maps the businesses (assumedly by name/legal name, since the WHD doesn't contain ID) to features about those businesses that could potentially be used to predict their risk for being a violator? We've been having trouble finding anything that characterizes a business other than its state and industry code
Tyrone Grandison • over 8 years ago
If I understand your question correctly, you are wondering if there is a way to get an attribute that you can use to join the data sources? If that is the question then the answer is "the current way that the enforcement officers do their jobs and collect data, there is no common attribute used in all cases. The best solution right now is to assume that canonical versions of (name and address) are the join attribute."
All the departments will one day collaborate and use a standard id.
After-thought: Maybe you can generate your own id using the Federal Contractor list (http://www.uscis.gov/sites/default/files/USCIS/Verification/E-Verify/E-Verify%20from%20Controlled%20Vocabulary/E-VerifyFedContrListandQueryVol.pdf) or a list of businesses using DUNS or another provider (http://developer.dnb.com/register)