Human trafficking and migration: Interview with Jacquelyn Meshelemiah
Bibliographic record
Abstract
Dr. Jacquelyn C.A. Meshelemiah is a Licensed Social Worker (LSW). She earned her Bachelor of Science in Social Work (BSSW), Master of Social Work (MSW), and Doctorate (PhD) from the College of Social Work, of The Ohio State University, USA. Dr. Meshelemiah has taught numerous courses across the curricula, but now exclusively teaches Assessment & Diagnosis in Clinical Social Work Practice, as well as Human Trafficking. She is the author and co-author of numerous publications, such as “Human sex trafficking” and, her latest, “Human rights perspectives in social work education and practice”. Has also done a series of presentations and trainings at the university, local, national, and international levels. Her primary research agenda centres on social justice, human rights, and anti-trafficking work. She has a crosscomparative analysis of human trafficking in Ghana, Uganda, Ethiopia, England, Mexico, Canada, Costa Rica, and the United States.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".