Charitable Legal Immigration Programs and the US Undocumented Population: A Study in Access to Justice in an Era of Political Dysfunction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines the legal capacity available to low-income immigrants on national, state and sub-state levels. Legal professionals working in charitable immigration service programs serve as the study's rough proxy for legal capacity, and undocumented immigrants its proxy for legal need. The Center for Migration Studies of New York (CMS) compiled data on charitable immigration programs and their legal professionals from the: US Department of Justice's (DOJ's) “Recognized Organizations and Accredited Representatives Roster by State and City,” which is maintained by the Executive Office for Immigration Review's (EOIR's) Office of Legal Access Programs (OLAP). Directories of two leading, legal support agencies for charitable immigration legal programs, the Catholic Legal Immigration Network, Inc. (CLINIC) and the Immigrant Advocates Network (IAN). CMS supplemented and updated these sources with information from the websites of charitable immigration programs. It also added legal programs to its dataset that did not appear in any of these lists. It counted as legal professionals, attorneys, federally accredited non-attorneys, paralegals and legal assistants. The paper finds that there are 1,413 undocumented persons in the United States for every charitable legal professional, and far less capacity than the national average in: States such as Alabama (6,656 undocumented per legal professional), Hawaii (4,506), Kansas (3,010), Georgia (2,853), New Jersey (2,687), Florida (2,681), North Carolina (2,671), Virginia (2,634) and Arizona (2,561). Metropolitan areas (MAs) such as Riverside-San Bernardino-Ontario (5,307), Dallas-Fort Worth-Arlington (4,436), Phoenix-Mesa-Scottsdale (3,439) and Houston-The Woodlands-Sugar Land (3,099). San Bernardino County (6,178), Clark County (4,747), Riverside County (4,625), Tarrant County (3,955) and Dallas County (3,939). The study's introduction summarizes its top-line findings. Its first section describes the importance of charitable immigration legal programs to immigrants, families and communities. Its second details the study's findings on charitable legal capacity and immigrant need. Its third compares the legal capacity of 1,803 charitable legal programs and their 7,322 legal professionals, with the US undocumented population by state and for the 15 largest MAs and counties. Its fourth describes CMS's research methodology and data sources. The paper ends with policy recommendations on how to expand legal capacity for low-income immigrants and better assess legal capacity and need moving forward.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it