The State of the American Child: Securing Our Children’s Future: Hearing Before the Subcomm. on Children & Families of the S. Comm on Health, Educ., Labor & Pensions, 111th Cong., Nov. 18, 2010 (Statement of Professor Peter B. Edelman, Geo. U. L. Center)
Bibliographic record
Abstract
You have asked me to reflect on the achievements and disappointments of recent decades with regard to child poverty in our country, on lessons learned, and on what we need to do going forward.\nIt is impossible to understand child poverty trends without placing them in a context of what has happened to the American economy and to the distribution of income and wealth. Except for the last half of the 1990s, the economic history of the past four decades has been one of near‐stagnation for people with jobs that pay below the median wage in the country ‐‐ the entire bottom half, if you will. Deindustrialization ‐‐ the flight of jobs abroad and the replacement of many jobs by automation – has hurt millions. Good paying factory jobs have been replaced (fortunately, new jobs did come along) by much lower paying service jobs. Half the jobs in the country pay less than $30,000 a year, and a quarter pay less than the poverty line for a family of four. Large numbers of children have grown up to get jobs that pay less than what their parents earned. Our economy did grow, but the increased income went almost entirely to people at the top of the income ladder. To cite just one stunning statistic, the top 1 percent took in 9 percent of personal income in 1976 and 23.5 percent in 2007. Understanding this framework is vital to understanding why we have not made more progress in reducing poverty over the past 40 years, as well as the larger situation of all lower‐income families and individuals. It is all far more rooted in the fact of low wage work and the ever‐growing gap between rich and poor than we typically say out loud.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".