Victims of Trafficking or Entrepreneurial Women? Narratives of Post-Soviet Entertainers in Turkey
Bibliographic record
Abstract
In June of 2002 I was invited as a casual observer to attend a workshop entitled Trafficking in Women sponsored by the International Organization of Migration in Istanbul Turkey. The workshop brought together a range of representatives of non-profits from Central and Eastern Europe to discuss efforts to curb trafficking in women. One presentation by a representative of La Strada a transnational non-profit dedicated to eradicating trafficking in women was characteristic of the two-day event. The speaker lamented the difficulty of warning hundreds of women travelling from Belarus and Ukraine to Germany who were not yet victims of prostitution about the dangers awaiting them. The speaker presented a computer game developed for use in Ukrainian schools; it featured Monika a cartoon figure as a potential victim of trafficking. Students were supposed to make choices-whether to accept work abroad or finish school whether to settle for a low-wage job or dream of economic prosperity abroad-and depending on these choices Monika was led to her doom or left safely if poor at home. (excerpt)
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.037 | 0.019 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".