North America: Growing Population Race Ethnicity and Religion(in Japanese)
Bibliographic record
Abstract
The U.S. population reached 300 million on October 2006, showing that the pace of population growth had not yet stagnated. The present study aims to answer the question of why among developed countries, almost all of which have entered into or are on the verge of a phase of population decline, the U.S. population alone continues to grow. In particular, the present study reviews demographic movement in the U.S. from the 1990s, focusing on fertility, death, and migration. In a supplemental chapter, the present study compares the demographic movement in Canada to that of the U.S. Demographic movement in the U.S. is often cited as an exceptional case compared to other developed countries. However, we have to understand that although this characteristic is an outcome of demographic diversity among ethnic, socio-economic, and religious groups, not every American exhibits exceptional demographic behavior. For example, the U.S. total fertility rate is now on a stable path around the population replacement level, after going through an eighteen-year-long baby boom after the Second World War, followed by a period of stagnation. Against the backdrop of its high fertility among developed countries, the U.S. has certain population subgroups whose fertility rates are very high and a uniquely flexible and adaptable social system. Moreover, the disparity in the mortality rates of population subgroups causes the U.S.'s high mortality rate compared to other developed countries. Additionally, about one million immigrants arrive in the U.S. every year, greatly contributing to demographic reproduction, as many are of a younger age group that is nearing reproductive age. The future demographic path of the U.S. is uncertain, reflecting the disparity between the converging and diverging trends of the demographic behavior of population subgroups; however, the U.S. population will continue to experience not only population growth but also demographic structural change.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".