Indoor Markets, Forward Migrations and Returns: The shifting contours of Nigerian Trafficking in Italy
Bibliographic record
Abstract
For many years Nigerian women represented one of the main national groups selling sexual services in the Italian street markets, with women of African origin making up around 45% of all women working outdoors throughout the country up to 2017 (NVA, 2023). Yet, around this time, and more significantly from 2019, their numbers started to progressively decline and, today, they represent only 16% of those selling sexual services in the streets (ibidem). This has left practitioners working in anti-trafficking organizations interrogating themselves on the factors that might have led to such a radical change. However, to this date, their questions have not yet found an answer. This presentation will retrace the main developments that the Nigerian trafficking phenomenon has gone through over the years. By presenting data collected through the conduction of semi-structured interviews, it will also explore the main hypotheses put forward by practitioners and experts working in the Italian anti-trafficking system to explain this radical change. In doing so, the paper will highlight how there probably is not a single factor that has led to the disappearance of Nigerian women from the street markets but, rather, a multitude of different ones that, combined, have contributed to it, such as secondary migratory movements towards other European countries, as well as a shift towards the indoor and ICT-mediated markets. Finally, the paper will explore another recent development within the trafficking phenomenon: Nigerian women’s requests for assistance to anti-trafficking organizations as they return to Italy after having spent several years in other European countries, and especially Germany and France, often after having experienced further exploitation in the sex markets.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".