The Influence of Culture and Values on Policy-Making and Teenage Pregnancy Rates in the United States, Canada, and Italy
Bibliographic record
Abstract
Abstract Ignoring the heated morality debates and millions of dollars invested in educational programs, the teenage pregnancy rate (and consequently the adolescent birth rate) in the United States remains the highest among the developed countries, even though it had decreased during the 1990s. Adolescent birth rates are 2.5 times higher than Canada's, and 7.2 times the rate reported by Italy. To account for the differences in teenage pregnancy outcomes among the three developed countries – United States, Canada, and Italy – a complex theoretical model of attitudes, beliefs, values, and policy decisions was constructed. Departing from the rational model approach, the present analysis emphasizes culture and values, and the way in which they influence the political process, and are ultimately reflected in the policy-making decisions. Data used to assess attitudes and beliefs prevalent in each of the three countries were obtained from the most recent release of the World Value Survey. Teenage pregnancy rates and other demographic data were drawn mostly from the World Bank's 2001 World Development Indicators. For the geographical analysis of the variations within the United States, data was obtained from the Center for Disease Control. The methodology combines cross-tabular and logistic regression analysis of individual attitudes and beliefs; a comparative table of social and economic indicators for a country-level analysis; a geographical information analysis (GIS) of the United States data; and a political analysis of the differences observed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".