Forced Marriage, Slavery, and Plural Legal Systems: An African Example
Bibliographic record
Abstract
Jody Sarich has seventeen years experience in research and advocacy of historical and contemporary slavery.She is the former Director of Research for the US-based international antislavery nonprofit Free the Slaves, where she oversaw participatory impact evaluation studies of antislavery interventions in India and Haiti and prevalence studies of slavery and forced labor in mining zones of Eastern Democratic Republic of Congo.She is currently working on a book, with Kevin Bales, about forced marriage based on her collection of the life narratives of forced marriage survivors and grassroots activists around the world, fiscally sponsored by Voices4Freedom Foundation.She received her M.A. in African History in 1999 from the School of Oriental and African Studies (SOAS), London, her J.D. from DePaul University School of Law in 2010, and is completing her Ph.D. thesis in African History on slavery in the Cape Colony.She was a member of the International Research Network to Define Slavery in International Law, sponsored by Queen's University, Belfast and the International Workshop on Forced Marriage in Conflict Situations, sponsored by York University, Toronto, and was on the
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.023 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".