Re-emphasizing the individual components of ‘child, early, and forced marriage’
Bibliographic record
Abstract
Efforts to eliminate ‘child, early, and forced marriage’, human rights violations with a wide range of harmful consequences, have intensified in the past twenty years as part of a growing social movement toward gender equality. The compound phrase ‘child, early, and forced marriage’ has become the preferred rhetoric in recent years and communicates a range of potentially harmful aspects of marriage, including the timing and consensuality of the event. However, we argue that two of the three component terms in ‘child, early, and forced marriage’ are not uniformly understood and, as a result, have not been adequately taken up in research, policy, or programming. In this review, we describe the history of this term and how different institutions define its individual components. We demonstrate that, in practice, ‘child, early, and forced marriage’ is often simplified to child marriage alone because this concept has a shared definition that is readily quantifiable. We recommend that clear definitions of early and forced marriage be developed and consistently applied alongside child marriage to further progress toward the overarching aim of improving gender equality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".