Ending Wage Theft in Los Angeles

submission by josh.goldstein.5494
Ending Wage Theft in Los Angeles

About Your Application

Organization(s) name(s):

Koreatown Immigrant Worker Alliance

Organization(s) website(s):


Organization(s) twitter handle(s):


Organization(s) facebook handle(s):


Please share the direct link for voters to sign up for your newsletter(s):


Describe Your Organization(s)

Non-profit organization

For-profit organization


Other (please specify below):

In one sentence, please describe what your organization does.


KIWA organizes low-wage immigrant workers, tenants, and their families to promote workplace justice, housing rights, immigrants’ rights, democratic and sustainable community development and civic participation.

In one to three sentences, please describe your proposal.


We seek to increase the resilience of low wage workers and their industries in LA by improving the enforcement of basic labor protections. We will design and pilot a wage theft prevention tool to help predict when and where wage theft occurs, so that City officials may wisely allocate resources to protect workers’ wages, and responsible employers from unfair competition. We will also produce industry case studies, to identify and learn from employers who create quality employment.

Where will you be working? Please be specific (e.g. Third Street Middle School; Boyle Heights; LA County).

Central LA

East LA

San Gabriel Valley

San Fernando Valley

South LA


South Bay

Antelope Valley

County of Los Angeles (countywide)

City of Los Angeles (citywide)


Other (please specify below):

How do you plan to use these resources to make change? (check all that apply)

Conduct research

Engage residents and stakeholders

Implement a pilot or new project

Expand a pilot or program

Mobilize for systems change

Advocate with policymakers and leaders

Implement and track policy

Other (please specify below):

How will your proposal improve the following “Live” metrics? (check all that apply)

Access to healthy food

Healthcare access

Exposure to air toxins

Number of households below the self-sufficiency index

Percent of imported water

Obesity rates

Housing affordability

Rates of homelessness

Walk/bike/transit score

Acres and miles of polluted waterways

Rates of mental illness

Prevalence of adverse childhood experiences (Dream Metric)

Percentage of LA communities that are resilient (Dream Metric)

Percentage of residents receiving coordinated healthcare services (Dream Metric)

Percentage of tree canopy cover (Dream Metric)

Describe in greater detail how you will make LA the healthiest place to live.


Each week, 30% of Angelenos in low-wage industries make less than minimum wage. 80% who work overtime aren’t paid for it; another 80% work through breaks. All told, wage theft siphons $26.2 million weekly from low-wage workers and the economy. Lost tax revenue robs the state of some $153 million annually, and local government of some $16 million.

The cost of wage theft isn’t just economic; it affects the health and well-being of communities. Each year, workers lose 12.5%--$2,070--from take-home pay of $16,500. This perpetuates poor housing and food insecurity. It exacerbates existing conditions like hypertension, diabetes, anxiety, ulcers, and depression. Workers struggle for additional hours to make up for lost wages, diminishing time for children, education, or self-care.

Enforcement is impossible in a climate of fear, yet Angelenos attempting to enforce their rights face a 50% chance of retaliation. This climate of lawlessness gives a competitive advantage to businesses who cheat. Employers who want to do the right thing can’t compete.

LA City and County voted to address economic inequality and stagnant wages by increasing the minimum wage. But without enforcement, as minimum wages increase, so will wage theft. New wage enforcement offices will need tools to handle the volume of violations when the new wage takes effect.

We propose a prototype to help identify the characteristics of 1) businesses in high-wage-theft industries that beat the odds to create good, healthy workplaces and 2) those who commit the most egregious violations. The prototype can inform policy to assist good actors and more effectively target businesses who bring our City down. It offers refined understanding of when and where wage theft occurs--as well as when and where businesses rise above. In a climate where retaliation is endemic, this promises a more inclusive process, helping identify violations where plaintiffs are afraid to come forward. We will share our prototype and convene conversations with the city, data scientists, and community groups. We will conduct case studies in high-risk industries to identify distinguishing factors between “high road” employers and employers with exceeding numbers of wage-theft complaints.

This partnership between KIWA; UCLA Labor Center; and Princeton researchers including the CEO of Department of Better Technology unites decades of on-the ground knowledge with employment policy expertise and data-driven analytical capacity.

Please explain how you will evaluate your work.


Our evaluation will answer three questions:

Does this save time?

Does this accurately predict violators and high road employers?

Does this help community based organizations and wage enforcement agencies allocate resources more effectively?

These questions will be measured through qualitative interviews with wage enforcement officials and community organizations, as well as with quantitative results from the prediction model.

How can the LA2050 community and other stakeholders help your proposal succeed? (check all that apply)

Money (financial capital)

Volunteers/staff (human capital)

Publicity/awareness (social capital)

Infrastructure (building/space/vehicles, etc.)


Technical infrastructure (computers, etc.)

Community outreach

Network/relationship support

Quality improvement research

Other (please specify below):

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Submission Began
Tuesday, September 08, 2015

Submission Ended
Tuesday, October 06, 2015
at 07:00 PM UTC

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Voting Began
Tuesday, October 20, 2015

Voting Ended
Tuesday, November 03, 2015
at 08:00 PM UTC

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Winner Announced
Tuesday, December 08, 2015