What is the Legal Services Corporation?
Established in 1974, LSC operates as an independent 501(c)(3) nonprofit corporation that promotes equal access to justice and provides grants for high-quality civil legal assistance to low-income Americans. LSC distributes more than 90% of its funding to 131 independent nonprofit legal aid programs with more than 890 offices.
What is the Office of Data Governance and Analysis (ODGA)?
LSC’s Office of Data Governance and Analysis provides LSC staff, legal and social services providers, policymakers, researchers, and the public with critical data to better understand the scope and extent of the civil justice gap, inform data-driven decisions, and expand access to justice for all. Our team is comprised of a diverse group of data scientists, data engineers, and researchers who use a variety of tools and strategies to make information related to civil legal aid more accessible and actionable.
What is the Civil Court Data Initiative (CCDI)?
LSC’s ODGA team launched the Civil Court Data Initiative in 2019 to gain greater insight into civil legal issues in the United States. The American civil legal system is based on a patchwork of laws, procedures, structures, and practices that can vary greatly by state/territory, county, city, and court. Furthermore, each court system collects, stores, and reports information on civil cases in a different way. These layers of complexity make it difficult to obtain basic information about the civil court system, such as the number of medical debt cases that are filed in a given year or the percentage of Americans facing eviction who do not have access to an attorney.
CCDI aims to fill this critical knowledge gap by creating a national repository of case records from civil courts across the country using cloud technology. This is the first initiative to collect and clean civil case records across numerous civil legal issues and jurisdictions (including U.S. territories) at such a large scale. The data we collect is used by organizations advancing local and national policy discussions regarding civil legal issues, including Princeton University’s Eviction Lab; the University of California, Berkeley; and the U.S. Census Bureau. CCDI is graciously funded by the Ford Foundation, the Andrew W. Mellon Foundation, and the Hewlett Foundation.
What types of data can I access on the site?
This website provides aggregate case information, including counts and rates for filings, legal representation, and judgments. These files have been crafted to meet the needs of a wide-range of audiences, including non-profits, academic researchers, and the media, who might not otherwise have access to clean, well-structured data about the cases proceeding through the U.S. civil court system. If you find the files available for download too difficult to work with, please contact us and we may provide you with more accessible files.
For all states/territories and a growing number of counties, the website also features eviction policy summaries that provide legal context for the information we provide from court data. LSC’s Eviction Laws Database includes more detailed information on eviction laws and procedures, including information for jurisdictions that are not yet available here.
Is there any way I can access the case-level data you analyze?
We provide a range of data on this website for public consumption to meet the needs of a wide range of audiences. These files include aggregate counts and rates that may be easily analyzed or visualized to understand trends. If you require case-level data for your work, we offer data-sharing agreements under which LSC may provide you more granular information about cases, parties, and events. Users are granted access to the data required for their specific investigation and LSC reserves the right to withhold personally identifiable information. LSC commonly enters into these agreements with academic researcher and federal agencies. Please email firstname.lastname@example.org if you would like to discuss entering a data-sharing agreements.
How does LSC collect data?
We collect civil court records from state and local court systems through multiple means. Primarily, we develop software to scrape extract information from public records from court record websites (known as “web scraping”). We also enter into data-sharing agreements with state courts to access their records, including purchasing records where necessary. LSC also accepts a small amount of data from individual developers scraping court records in a local context.
Eviction policy summaries are constructed from state/territory statutes, county and municipal codes, court rules and procedures, and guidance from local legal aid providers and court officials. For more information, please visit the Methodology page.
How do you ensure your data is accurate?
We strive to provide data that is representative of the full caseload that courts process. To measure how closely our data mirrors the full caseload, we compare the number of cases filed per year by county and by case type in our database to the number of filings that courts list in their annual reports. We have compiled the Baseline Court Statistics dataset, which contains county-level filing counts from over 30 states from annual statewide court reports. We have made this dataset available to the public for others to use for secondary analysis. You can find this dataset and a codebook available here.
There are numerous reasons why the data we collect might be inaccurate or may differ from the official counts reported by courts. Some of these issues may come from the courts themselves due to variation in case data entry processes or policy/system changes. Others may result from data processing issues when we gather or process records from courts.
Some examples of court-related data issues include:
- In some jurisdictions, certain cases are sealed or masked at some point after they are filed to protect the privacy of the parties involved in the case, meaning that these case records are not made available to the public. For example, a jurisdiction may have a law that seals any eviction case that does not result in the tenant being removed from the rental home in order to protect the tenant from future housing discrimination. If a jurisdiction automatically seals some cases after filing, the number of cases scraped from a public court website might differ significantly from the number ultimately reported in the court’s annual report.
- Courts have migrated from physical to digital records over the past few decades. In some jurisdictions, older cases have not been fully digitized and will not be available for incorporation into our database. As a result, our database may have no data or incomplete data for these jurisdictions in years prior to 2016, even if aggregate case data is available through official court reports.
- Courts occasionally change case types in response to new state and local laws and policies. For instance, the case types associated with eviction in Florida has changed at least twice since 2016. We continuously monitor case types to ensure they are recoded properly; however, some case types will not be recoded immediately and might lead to inaccurate filing counts for a period of time.
Some examples of data processing issues:
- When scraping court records, we must systematically identify every case filed within the time period of analysis. Most court websites allow you to enter a range of dates for which the website will return all cases filed between those dates; however, some websites do not provide this functionality. For locations that do not provide this option, we must determine how the courts assign case numbers and construct all possible case numbers (see the Methodology for more details). If a court system changes the numbering system or does not strictly follow this numbering system then our software will not capture the full caseload.
- Each court website structures data differently. One court might identify eviction cases under the case type “unlawful detainer” while another will identify these cases under “forcible entry and detainer”. We must reclassify these case types to a single taxonomy to facilitate analysis. While we take great pains to classify case types accurately, we might make mistakes which would lead to inaccuracies in the data and visualizations we produce.
For eviction policy summaries, our team follows best practices in policy surveillance research to ensure the information we present accurately reflects the reality of eviction in each jurisdiction. However, there are limitations to this work. Because of the complex nature of the U.S. civil justice system in general and eviction in particular, our researchers must routinely review and analyze many layers of laws, procedures, and case law to understand the nature of eviction in a particular jurisdiction at a given point in time. To complicate matters further, many jurisdictions (particularly in rural areas or in U.S. territories) do not have the resources to post and regularly update their local eviction policies online or in other readily accessible formats. To address these concerns, our team has formed partnerships with local legal aid providers, court officials, and other experts who help to review and correct our eviction policy information. If you have concerns about the accuracy of any information in our eviction policy summaries, please reach out to us at email@example.com.
Why is there no data for my jurisdiction?
We are actively working to add data from more jurisdictions, however there are some fundamental data access limitations. Not all courts make records publicly available online in a manner that facilitates data collection. Similarly, local-level eviction policies are not always made available online by county/municipal governments or court officials. In these locations, we are exploring other means to gather data, such as working with partners on the ground to compile this information. If you are interested in helping make data more available in your community, please reach out to us at firstname.lastname@example.org. If you work in a court system and would like to contribute data, we would love to discuss how to integrate data in a way that is easy for you.
How am I allowed to use or redistribute the data?
You are free to use the data available on this website in any way you see fit. We request that you cite the data as follows: Civil Court Data Initiative. Legal Services Corporation, 2022. (accessed TODAY’s DATE).
Do you only collect eviction records?
No, we collect all civil court records. The specific case types we collect varies by jurisdiction, but we generally collect data on eviction, debt collection, garnishment, domestic violence, probate, and family law cases. We do not collect data on traffic or criminal cases. If you have questions about what types of data we collect in a particular jurisdiction, please reach out to us at email@example.com.
If some jurisdictions enter data manually, how up to date are the data? Is there any lag? Each of our methods of data collection carry some degree of lag. For data that we scrape from public records, there is often a lag between when a case is filed and when it becomes available on a public court website due to processing delays. We periodically re-scrape court records to ensure we capture all cases filed on a particular day.
In jurisdictions where we collect data from public dashboards, our data is only as current as the data in these resources. For example, if a dashboard provides the monthly eviction filings for each county in Kentucky, we may not have the current month’s data until next month or later depending on how often the dashboards are updated. We receive some datasets on a weekly or monthly basis directly from the courts; these datasets will have an inherent lag where data from the most recent week or month is not included in our estimates.
Can I get information about parties, judgments, or other parts of the case record?
In most jurisdictions, we collect extensive information about the cases, parties, judgments, and other events that occur in civil court cases. We will continue to make aggregate data available to the public on this website; however, you might have data needs that go beyond the data we currently make available. If the data provided is not sufficient for your work, please reach out to discuss other data access options.
Is it possible that historical data could change after I last looked at or downloaded it? Yes, the data is subject to change at any time due to changes or updates in individual case records from the courts. In addition, policy changes that result in cases being hidden or revealed (i.e., case sealing/masking laws) may also cause a change in the data you see presented on this website. We strive to provide timely information about any changes in the data through the revision history. If you notice large changes between the data you download and the data that appears on the website at this time, please reach out to us at firstname.lastname@example.org and include information about when you downloaded the data.
Can I subscribe to get updates for my jurisdiction?
You can subscribe to our newsletter on the Contact Us webpage to learn about new additions and updates to the data.
Is there an API I can use to pull data for my jurisdiction?
We do not provide API access to data at this point. If you would like to see this functionality provided, please reach out to us to discuss your use case.
What should I do if I suspect a discrepancy in the data?
If you identify or suspect a discrepancy, please reach out to us at email@example.com to discuss the issue.
How should I cite use of the data?
We request that you cite the data as follows: Civil Court Data Initiative. Legal Services Corporation, 2022. (accessed TODAY’s DATE).
What’s the difference between eviction filings and evictions?
In general, we can define an “eviction” as an attempt to forcibly displace a tenant who lives in a rental property. Evictions can be broadly classified as being “formal” or “informal”.
Formal evictions are those that occur within the civil legal system, as per the laws and procedures defined by state/territory and local governments as well as courts. The first documented step of the formal eviction process occurs when a landlord or property manager files an eviction case with a court; this tells the court that the landlord or property manager (plaintiff) wants to sue the tenants living in the rental property (defendants) in order to force them to leave the property. In other words, one eviction filing equals one law suit. We use the number of eviction filings to count how many times landlords or property managers tried to sue tenants living in a given community, county, or state/territory. However, the number of filings alone does not tell us anything about what happened in those eviction cases. Even if a landlord or property manager files an eviction case, the case may be dismissed or the court may rule in favor of the tenant, allowing the tenant to continue residing in the rental property.
Informal evictions are those that occur outside of the legal system. This does not necessarily mean that they were performed illegally, but rather that there is no official documentation of the eviction taking place. As a result, informal evictions are notoriously difficult to quantify. For more information on informal evictions, please see this piece by New America.
How do you define legal representation?
Court records identify legal representation in many ways. Many court record systems will identify the attorney representing each party by name and some will also include the attorney address and bar number. For parties that do not have attorney representation, some court systems will explicitly identify these parties as “pro se” or “pro per”; however, the majority of systems will leave the field empty. In this scenario, we assume that the party is unrepresented if the field is empty. It is possible that the party is represented but the attorney information was not entered into the court record; we are unable to ascertain the extent of this issue in the data. Please see the Methodology page to learn about how we validate representation consistency.
Legal aid organizations provide levels of legal representation ranging from basic legal education to full legal representation in the courtroom. The data CCDI collects only includes the cases where attorneys have been formally entered into the court record on behalf of a party. This data will underplay the full impact legal aid organizations have in their communities because the data only captures the cases where a legal aid attorney was entered into the court record. For more information about the fuller impact of legal aid organizations, please see Our Grantees webpage and LSC’s Justice Gap Report, specifically Section 6: Reports from the Field.
Additionally, tenants are not always fully represented throughout an entire case. Court records do not often distinguish between parties having representation in all hearings versus only one. The statistics here count a party as represented if an attorney appears on their behalf at any point in the court record.
How do you define a judgment?
Court record systems do not report judgments in a uniform manner. Some courts explicitly label the final judgment, while other systems list the judgment as one entry among many events in the case history. In the former scenario, we can easily parse the judgment from each case record. The latter presents a more challenging case because we must use keyword searches to distinguish between actual judgments and other related events (such as motions for judgment) and establish the reliability of these keyword searches to identify the judgment across the dataset. For instance, we might determine that searching for the term “judgment for plaintiff” identifies all cases containing a judgment for plaintiff. However, upon further investigation, we might discover that some cases use shorthand for the same event (“jdgmt for pltf”); fully capturing the variation in how judgments are entered is nearly impossible.
Cases might also contain conflicting judgment events. For example, an eviction case might display a default judgment and then the case was voluntarily dismissed a week later. This sequence of events might indicate that a tenant vacated a property after the default judgment but before a writ of restitution was executed, the landlord might then dismiss the case after the tenant vacates.
We attempt to reconcile conflicting events by processing judgments in a priority order. If we identify a default judgment event, we will classify the judgment as a default judgment despite other potential judgment events in the case (such as in the example previously described). If no default judgment event exists, we will then identify any dismissals. We continue to iterate through a set of judgments until one is identified. If no judgment is identified, the judgment will be left empty (or null).