Equal Access to Justice for All People? An Investigation of the Factors Driving the Distribution of Civil Legal Aid Grants

Joanna Schroeder, William & Mary


1. Purpose

This study is concerned with investigating the political, need-based, and capacity factors that drive the allocation of civil legal aid grants to organizations.

3. Literature Review: Need-based, capacity, and political explanations

3.1 Demand-side explanations

For the issue of civil legal aid, several factors, including not only community need for civil legal aid, but organizational and environmental capacity, comprise the demand-side.

Need-based factors

Poverty level is one of the greatest indicators of need for civil legal aid. According to the Justice Gap survey report, 71 percent of low-income households experienced at least one civil legal problem in 2016, and, because of a lack of resources, half of low-income Americans who seek legal aid for their issues will receive limited or no help. While poverty overall can be considered a barrier to justice, as it directly impacts an individual’s ability to afford legal counsel or qualify for aid, there are other practical barriers to justice associated with being in poverty. Other factors such as population density, education level, primary language, race and ethnicity, and access to high speed internet can all affect civil legal aid need.

Capacity factors

Recipient capacity describes the applied organizational and environmental factors that affect the allocation of civil legal aid. Capacity is critical to understanding the distribution of aid because donors, whether private or public, are ultimately concerned with their grants being used effectively and producing results. Organizational capacity describes the factors within an organization that influence the receipt of grants, such as revenue, number of employees, or number of volunteers. The other main piece of defining recipient capacity is the environmental capacity of organizations to receive grants, or factors surrounding an institution that can influence its ability to receive grants. Environmental capacity includes the affluence of the community surrounding a legal aid clinic and competition from nearby clinics.

3.2 Political explanations

In political science, theories of distributive politics describe how not only how government resources are allocated, but why they are allocated that way. Often, political explanations for resource allocation are juxtaposed against demand-side explanations, showing that political factors often drive resource allocation to inefficiency. While the most common distributive politics explanations focus on political factors in legislative bodies, as the appropriating committees, some theories describe the power of the executive branch in driving decisions of resource allocation. In the case of civil legal aid allocation, it is important to look at the amount of funding received by organizations located in a Congressional district represented by a member of LSC’s appropriating committee (Commerce, Justice, and Sciences) to see if there are political biases involved with public aid allocation. Fig 2. Factors Driving the Allocation of Civil Legal Aid

4. Data and Methods

The data for this study was collected from the Foundation Directory Online, a database containing observations of grantmaking for a variety of sectors including health, the environment, and legal aid. The results of this search were webscraped using Selenium Webdriver through Python, creating a datatable of information at the grant level of recipients, grantmakers, and grant information. Among the information attained was organization Employer Identification Number (EIN), a unique identifier used by the IRS for tax administration. The obtained EINs were fed into ProPublica’s nonprofit API so that organization information, including annual revenue, could be coded into the dataset. Additionally, addresses for each business were folded into the dataset for precise location information. The addresses were geocoded using the TAMU geocoder. Political and demographic information for each recipient organization was folded into the dataset using their locations.

The three dependent variables analyzed were: 1. Total Amount ($) of Grants. 2. LSC (Dummy). 3. Amount ($) of Grants from LSC.

4.1 Methods

This analysis used penalized, OLS, and geographically weighted regression to model the effect of the explanatory factors on the three outcomes of interest. The complementary methods approach of this study allows for a nuanced analysis of the data, where the strengths and weaknesses of several methods are balanced out to understand a more holistic picture of civil legal aid distribution.

4.2 Hypotheses

  1. Capacity will be the most influential factor in civil legal aid allocation for the amount ($) of grants for the entire network.
  2. Capacity will be the most influential factors in the receipt of aid from LSC.
  3. Community need-based factors will be the most influential factors in civil legal aid allocation for the amount ($) of grants from LSC.
  4. Political factors will not be influential for any of the outcomes of interest.

5. Analysis

5.1 DV 1: Total Amount ($) of Grants

The analysis of DV 1 showed that the model was not very well specified. Overall, organization revenue was the most significant factor the model. The GWR analysis showed that there is some geographic nuance with the need-based variables, showing patterns of both positive and negative relationships across the country.

5.2 DV 2: LSC (dummy)

The model for analysis of DV 2 was better specified than the previous model. Overall, capacity factors continued to be the most influential, with the most significant relationships being between organization revenue and competition within 10 miles and the outcome of interest. The GWR analysis showed mixed support for both need-based and environmental capacity influences on allocation of public civil legal aid.