On Exiting from Commercial Sexual Exploitation: Insights from Sex Trade Experienced Persons
Bibliographic record
Abstract
As a woman who exited after seven years in licensed commercial sexual exploitation in Canada, I share my reflections on my experience, which led to the development of the Insights from Sex Trade Experienced Persons (InSTEP) Model. The model was constructed based on interviews with “service providers” in the sex trade. Twelve exited women share their experiences inclusively. InSTEP is geared toward a population of quasi-autonomous providers who have alternate economic options. Three levels are introduced in the InSTEP model to describe the continuum of agency among service providers; Level 1: trafficked/controlled; Level 2: quasi-autonomous; Level 3: autonomous. The InSTEP Model focuses on Level 2 providers and identifies optimal times when helping professionals or agencies could be most effective in offering exit support. Opportunities for change are contextualized within Maslow’s Hierarchy of Needs (1943) and the Prochaska and DiClemente’s (1983) Stages of Change.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.020 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.008 |
| 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".