Prototype for an SMS-based Bad Date List
Bad Date Lists have been around for a long time. These lists, which typically manifest as handwritten or printouts of information about bad dates (explained in a moment) gathered by outreach workers as well as sex workers, have been the primary form of distributing the data. In recent years, password-protected website forums and email listservs have also served to disseminate information. In terms of sex work, a bad date refers to a client or law officer (who may also be a client) who has wronged the sex worker in some way. The most common reasons for ending up on a bad date list include refusal to pay, haggling, aggression, stalking, physical or verbal assault, threats, and/or sexual assault or rape.
This information can become out of date quite fast and is limited to geographic areas for print outs and to workers with access to the internet. The reality is, clients travel and so do workers. The idea has been around for a while to create an SMS based-bad date list. There are a number of factors that go along with this new technology:
- How should subscribers be screened?
- How can the data be kept out of the wrong hands?
- How can the data be kept private and safe?
- How can users and developers avoid legal complications form using the service?
- How can the BDL (bad date list) in an SMS-format be developed on a technical level?
As a harm reductionist, community organizer, and technologist, I decided to take on this challenge. Initially I was planning on developing a system for students who receive packages at my graduate program to be pinged by SMS to notify them when a package arrives. However, I decided to give the SMS BDL a try instead for my Mobile Me(dia) class.
Thus far, I’ve been able to receive SMSes and have them written into a PHP MySQL database and furthermore, displayed on a website. The phone number of the person who texts in the information will be omitted but the information they provide will be displayed. I am still figuring out how to add a time/date stamp and how to send data back to subscribers based on keywords such as zipcodes for geographic location.
My prototyping page can be found here.