Economic Mobility or Safety Net? Examining Employment Status and Wage Trajectories of Housing Choice Voucher Recipients
Bibliographic record
Abstract
This study examines employment status and wage trajectories of recipients of the Housing Choice Voucher (HCV) program from 2005 to 2018. Drawing on a national dataset containing 22.5 million householder-year observations, the research underscores the dual role of the HCV program as both a safety net for housing stability and a potential tool for economic mobility. The findings reveal that nearly three out of four voucher householders in the sample were not employed in any given year after entering the program. Additionally, over half of the householders (53.8%) never earned wage income during their participation in the HCV program. While a subset of voucher recipients who consistently earned wages experienced wage growth – contrasting with national trends of wage decline among similar income groups during the same period – the average absolute wage remains modest. Furthermore, the study highlights that the HCV program’s impact on economic mobility is uneven and varies significantly across demographic subgroups. These findings underscore the importance of recognizing the HCV program as first and foremost a policy that guarantees stable housing serving many individuals in need of permanent housing support who do not participate in the labor force. Policies aimed at HCV program exit should be targeted to the smaller group of voucher recipients who are able to participate in the workforce and focus on supporting these households’ employment goals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".