Growing up in North America: Child well-being in Canada, the United States, and México
Bibliographic record
Abstract
The premise of the Children in North America Project lies in the kind of world we live in today, an increasingly interdependent, complex, and connected world. It is a small world where school children living in a desert state or a prairie province know all about a tsunami because of images of wreckage from a giant wave half a world away. As the globe shrinks, so too does North America. The continent that is shared by three nations, each with its own proud history, is becoming more economically, socially, and culturally integrated- through trade, investment, communications, human migration, education, travel, and cultural exchange. Children in the three nations are increasingly being exposed to similar consumer goods, media messages, and social trends. Moreover, for some children, increased economic ties imply drastic changes to their immediate surroundings and prospects - whether it is a child living in an American family without work because the local employer moved its operations to Mexico or a child living without a father in a Mexican town because many working-age men have left to seek jobs in the United States or Canada. The sheer scale of migration from Mexico to the United States and, to a lesser extent, to Canada is changing the face of the region and the lives of countless children. The Mexican-born population in the United States more than doubled between 1990 and 2000, going to over 9 million people, according to U.S. Census data. Remittances from Mexicans working in the United States to families back home amounted to over 16 billion U.S. dollars in 2004 (as estimated by the Central Bank of Mexico), roughly 1.5 percent of the country's GDP. Added together, the sums that migrants send back home surpass Mexico's revenues from tourism, foreign aid, and foreign direct investment. The Children in North America Project is exploring these new realities. It is building a new knowledge base about children across the continent. That knowledge base includes measures of child well-being and the local, national, and tri-national contexts or environments in which families live. These data tell the story of a diverse population of children characterized by profound differences in their well-being and security both within countries and across the region. Through this project, we hope to build a better understanding of how our children are faring and the opportunities and challenges that they face looking to the future. Our goal is to inspire and mobilize action to make the lives of all children in North America better, to ensure that no child is left behind.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; a candidate call from one teacher head, 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".