Prevalence, responses, and strategic interventions of pregnancy in childhood and adolescence in South Africa
Bibliographic record
Abstract
While the education system’s response to pregnancy in childhood and adolescence has been to ensure that pregnant teenagers attend school before and after childbirth, the criminal justice system has set grounds for civil and criminal proceedings for fathers who impregnate girls under the age of sixteen. However, both the education and criminal justice systems remain silent about the prevalence, responses, and strategic interventions towards alleviating pregnancy in children and adolescents. This study aimed to review the prevalence, surrounding discourses, and ways of responding to pregnancy in children and adolescents in South Africa. Data mining from local and international literature and governmental organizations were consulted to determine the estimation of pregnancy in childhood and adolescence. Foucault’s pedagogization of children’s sexuality underpinned the study. Pregnancy in childhood (as early as reported at age 9) remains a silent phenomenon due to the false notion that children are incapable of childbearing, a myth that further exacerbates their risk of early pregnancy. Intergovernmental strategies regarding how education and criminal justice systems can appropriately address and manage the rising occurrence of pregnancy in childhood and adolescence are discussed. Recommendations for policy implementation are outlined in response to the growing rates of pregnancy in childhood and adolescence.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".