Contemporary public policy towards prostitution regulation on a global scale

Looking back at the hypotheses, I can establish the following:

H1 is successfully refuted, as it could predict and there is no significant differentiation between abolitionist and criminalized regimes.

H2 cannot be confirmed by any interpretation of this analysis - at the point where a line between full and partial criminalization can be drawn, too many smaller outlier categories (even if I can't be sure of consistency of specific groups) appear that were not predicted by this type of classification, and overall few clear boundaries can be seen even between broad categories such as full or partical criminalization.

H3 is validated, specifically with the Цstergren's classification. The only consistent pattern that appears in the data is the separation between regimes that give some legal avenue for prostitution while criminalizing others and the regimes that try to eliminate or repress prostitution wholesale, and this distinction is consistent with Цstergren's distinction between “Repressive” and “Restrictive” regimes. While “Integrative” model is not accounted for in the data, this actually is consistent with the classification as the author herself acknowledges that this model has not yet been implemented to a meaningful extent.

Conclusion

The idea of this paper came up when I realised that all comparative research of prostitution policy, including mine, is wholly reliant on a set of conflicting classifications, whose verification has not even been attempted. A systematic, practically applicable comparison of prostitution policies required a typology that is not only unambiguous and non-overlapping, but also reflective of the policies studied - if such typology could be found at all. In this paper I have identified commonly used prostitution policy classifications and shown that they tend to be imprecise and incompatible, and that even the best of them would benefit from practical testing. While Цstergren's classification was clearly a step forward from the onset, the possibility of a more specific and more practical classification based on global data was still a possibility that had to be analyzed. However, the data - to the extent I could gather and analyze it - has not yielded answers any easier that I had before working with it. It can be indicative of the idea that something was missed, and improvements in operationalization or analysis could provide us with a simple and useful classification that has not been seen before. It can also mean that there is simply not enough difference either in the laws that the countries around the world apply to prostitution, that laws, “legality” or “illegality” of prostitution or its aspects are not a good enough approximation of the relationship between it in the state in different countries. I believe that the latter is the case (although some personal investment in that option has to be admitted), even though most of non-specialist policy discourse is centered around the laws and the possibility of their change. While the dataset that was created for this paper can be useful for both large-n (connections between prostitution policies and broader political and economical factors such as GDP or state capacity) and small-n (as a source of most-similar or most-different comparative case studies) research, I urge any researcher that reads this to look beyond laws and beyond quantitative data - to implementation, to intents of people writing laws and people enforcing them, on experiences of people involved in the industry, native and non-native. The policy question that needs answering is not “Should prostitution be legal?”, it is “What should states and societies do to minimize prostitution's inherent risks and negative impacts?”. Цstergren's protocol of assessing intents, instruments, implementation and impact of a prostitution policy would be instrumental in answering this kind of a question. This paper has additionally illustrated the necessity of such deeper approaches.

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Appendix

Dataset of Prostitution Policies

Dengrograms of Prostitution Regimes (without selected clusters - on the left; with primary clusters used in the interpretation - on the right)

Dendrograms of sampled clusterings (70% of the dataset, cutoff dissimilarity level similar to the main 6-cluster interpretation)

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