Women's Changing Commutes: The Work Trips of Single Mothers in the New York Region, 2000–2010
Bibliographic record
Abstract
Single mothers are an important and growing segment of the U.S. workforce. As primary breadwinners and caregivers, they shoulder a 'double burden' that often constrains their access to job opportunities and reinforces their commuting challenges. In the urban areas where most single mothers live, ongoing transformations of the built environment associated with gentrification and uneven transit investment may exacerbate their commuting challenges. We examine the impacts of built environment characteristics on single mothers' reliance on various transportation modes for their commuting trips in the New York metropolitan region. Our analysis focuses on changes in mode use during the 2000s, a period of rapid change in the region's built environment. Using microdata from the 2000 and 2008–2012 U.S. Census PUMS, we analyse geographic and racial/ethnic inequalities in single mothers' mode choices and the socioeconomic and contextual factors that influence transit dependence. Our results show that transit use is increasing both among single and married mothers, as working mothers shift away from commuting by car. At the same time, single mothers increasingly live in suburban and peripheral areas where access to transit is limited. Although only a relatively small percentage of suburban single mothers commute via transit, that percentage increased from 2000 to 2010. Transit dependence is especially high among minority single mothers and that disparity persists after controlling residential location, transit access, hourly earnings and sociodemographic characteristics.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
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".