Bibliographic record
Abstract
Adolescent pregnancy in youth aged 10-19 years is associated with higher rates of adverse outcomes for both the mother and infant than adult pregnancy. Obesity and immature pelvic growth compound the associated risks of adolescent pregnancy. Black and Indigenous youth in the United States (U.S.) experience disproportionately high rates of adolescent pregnancy and obesity. This research project aimed to answer two questions: (1) What are the contributing risks of pelvic immaturity and obesity on adverse outcomes in adolescent pregnancy, especially in the U.S.?; and (2) Why are Black and Indigenous youth at particular risk of adolescent pregnancy and obesity in the U.S.? In this research project, I have conducted statistical analyses of biological and sociocultural factors associated with adolescent pregnancy using the CDC WONDER database, and I have used case studies and ethnographic accounts to gain insight on Black and Indigenous youth experiences with adolescent pregnancy. In this paper I examine the racial disparities in rates of adolescent pregnancy, obesity, and adverse outcomes in the U.S. My paper contributes research to a current public health issue by using an integrative biocultural approach.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".