Analysis and mapping of literature on child marriage published in peer-reviewed journals (1983 – 2022)
Bibliographic record
Abstract
Child marriage, a stark disruption of the traditional childhood experience, remains a pressing concern, yet the scientific exploration of this complex issue has been surprisingly overlooked in terms of comprehensive analysis and mapping. This study aimed to bridge this gap by conducting an extensive examination and mapping of child marriage literature within peer-reviewed journals. Employing the powerful Scopus database, the study combed through research articles spanning from 1983 to 2022. Both quantitative and qualitative analyses were applied to uncover research trends and content patterns. The search string led to the retrieval of 964 relevant documents, revealing a nearly equal distribution between medical and social science subject areas. The analysis yielded several crucial findings. Firstly, it became evident that the current volume of research on child marriage, considering the prevalent rates and impact, falls considerably short of being adequate. A notable surge in research output was detected in the most recent five-year span (2018–2022), likely in response to the global commitment to sustainable development goals. Despite countries with high child marriage rates contributing relatively less to the research landscape, specific nations like India, Bangladesh, Ethiopia, and Nigeria left a noticeable imprint. Furthermore, high-income countries, including the US, the UK, Canada, and Australia, demonstrated significant involvement primarily through international research collaborations with scholars in high child marriage rate regions. Equally noteworthy is the revelation that the field of child marriage is a convergence of scholarly efforts from both the social and medical sciences. Notably, the University of California San Diego played a pivotal role in shaping and fostering research in this domain. In conclusion, the urgency of eliminating all detrimental practices against girls necessitates heightened research efforts, deeper collaboration, and a more holistic 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 | 0.009 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.170 | 0.181 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".