“My Dollar Doesn’t Mean I’ve Got Any Power or Control over Them”: Clients Speak About Purchasing Sex
Bibliographic record
Abstract
Within contemporary global debates on sex work laws, clients of sex workers are a central focus. While punitive legislation used to regulate the sex industry has a long history of targeting sex workers, policy makers are now increasingly directing their attention to clients as the targets of criminalisation. As Sanders (2008) explains, ‘there has been a repositioning of men who buy sex as the problem’ (p 135). That is, clients of sex workers are increasingly being depicted as sexual abusers, and the abolitionist feminist perspective that sex work is a form of male violence against women appears to have gained more support (Bernstein, 2007; Coy et al, 2019). As such, policy makers in many countries have opted to enact new laws which criminalise the purchase of sex, including Sweden in 1999, Norway and Iceland in 2009, Canada in 2014, France in 2016, Northern Ireland in 2015, and the Republic of Ireland in 2017 (Serughetti, 2012; Arisman, 2019; Calderaro and Giametta, 2019; Coy et al, 2019; McMenzie et al, 2019). This approach is often referred to as ‘the Swedish model’ – owing to its initial adoption in Sweden – and also ‘the Nordic model’ since versions of it have now been adopted in several countries in the Nordic region. As noted by McMenzie et al, (2019), between 2012 and 2014, Northern Ireland’s Democratic Unionist Party campaigned to introduce client criminalisation through drawing on Sweden as a source of inspiration and as a country to be learnt from and emulated. Likewise, when sex work regulation was debated in France during 2011, a key report presented to the National Assembly for parliamentary debate argued that the onus for sex work should be located with clients, as their demand for paid sexual services fosters exploitation and trafficking (Calderaro and Giametta, 2019).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".