Forgotten Families: Ending the Growing Crisis Confronting Children and Working Parents in the Global Economy
Bibliographic record
Abstract
In the last half-century, radical changes have rippled through the workplace and the home from Boston to Bombay. In the face of rapid globalization, these changes affect us all, and we can no longer confine ourselves to addressing working and social conditions within our own borders without simultaneously addressing them on a global scale. Based on over a thousand in-depth interviews and survey data from more than 55,000 families spanning five continents, Forgotten Families is the first truly global account of how the changing conditions of work threaten children, women and men, and the infirm. It addresses problems faced by working families in industrialized and developing countries alike, touching on issues of child health and development, barriers to parents getting and keeping jobs, problems families confront daily and in times of crisis, and the roles of growing inequalities. Rich in individual stories and deeply human, Heymann's book proposes innovative and imaginative ideas for solving the problems of the truly belabored together as a global community. Available in OSO: http://www.oxfordscholarship.com/oso/public/content/politicalscience/9780195335248/toc.html
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".