Failing the Transition from Welfare to Work: Women Chronically Disconnected from Employment and Cash Welfare<sup>*</sup>
Bibliographic record
Abstract
Objectives. Although employment among welfare mothers increased substantially following the 1996 welfare reform, some former welfare recipients failed to find stable employment. We review the extent to which low‐income mothers are without work and cash welfare for long periods of time and seek to understand the correlates of becoming chronically disconnected. Methods. We analyze data from a 1997–2003 panel study of single mothers who received cash welfare in an urban county in Michigan in February 1997. We develop a new measure of the extent to which former recipients are “chronically disconnected” from both employment and cash welfare and estimate regression models of the correlates of this economic outcome. Results. About 9 percent of respondents became chronically disconnected, defined as being without employment and cash welfare during at least one‐quarter of the months during the 79‐month study period. Important correlates of becoming chronically disconnected include having a physical limitation, having a learning disability, using illegal drugs or meeting the diagnostic screening criteria for alcohol dependence, and having no car or driver license. The chronically disconnected are more likely to have lost a job than to have lost welfare benefits and are more economically disadvantaged than those with regular sources of economic support. Conclusions. To reduce the number of women who fail to make a successful transition from welfare to work, more attention should be given to programs and policies that attempt to reconnect disconnected women to regular sources of economic support.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".