P3.308 The Changing Male Sex Worker Population in London (2002 – 2012)
Bibliographic record
Abstract
Background With freedom of movement across European borders, increasing globalisation and emergence of new major economies, the UK has seen significant changes to the composition of nationalities migrating to the UK over the last ten years. In turn this has changed the working population of the UK. The objective of this study was to investigate the changes in nationalities of male sex workers (MSW) attending a dedicated clinic for MSW in London over the last decade. Methods Clinic records for MSW attending a dedicated clinic in Central London were reviewed (1/1/2002 – 31/12/2002 and 1/1/2012 – 31/12/2012). Details of country of birth and nationality were collected for each attendee. Data was compared for each time period and grouped according to geography, and for Europe, according to traditional East - West borders. Results Data was available for 211 men in 2002 and 230 in 2012. Country/region of birth (shown as % 2002, % 2012) was UK (37%, 43%), Western Europe (21%, 12%), Eastern Europe (6%, 6%), Latin and South America (15%, 31%), SE Asia (3%, 4%), Middle East and North Africa (3%, 0.4%), Sub-Saharan Africa (6%, 2%), USA and Canada (1%, 0.4%), Australia and New Zealand (4%, 0.4%), Other (3%, 1.3%). Conclusions Nationalities of MSW attending the dedicated clinic in London have changed dramatically over the past decade. Though the majority remain UK born (37% in 2002, 43% in 2012), MSW attending from Western Europe (excluding UK) have fallen markedly (21% to 12%). The most notable increase in this period has been the number of MSW from Latin and South America (15% to 31%), the largest proportion being Brazilian (13% of total attendees in 2002, and 27% of 2012). Brazilians now account for over a quarter of MSW clinic attendees and MSW services need to adapt to support this cohort.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.050 | 0.011 |
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".